Smart traffic control devices and beacons, methods of their operation, and use by vehicles of information provided by the devices and beacons

ABSTRACT

A smart traffic control device implements a method for detecting faulty sensors that result in false green requests and/or undetected true green requests. The faulty sensors may include inductive loops and pedestrian pushbuttons. The traffic control device may communicate with remote resources, including computer systems connected to human resources, to help identify the faulty sensors. The human resources may be crowdsourced. The traffic control device&#39;s communications with the remote resources may go through vehicle computers and smart phones of vehicles&#39; occupants and pedestrians. The traffic control device may emit signals to enable vehicle computers to improve accuracy of position location. The traffic control device may emit its state (e.g., Green/Yellow/Red in various directions) and time to state changes, in real or substantially real time. A vehicle computer may receive the state and/or time to state changes and vary operation of the vehicle&#39;s power train in response thereto.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Patent Application Ser. No. 62/596,891, entitled SMART TRAFFIC CONTROL DEVICES, METHODS OF THEIR OPERATION, AND USE BY VEHICLES OF INFORMATION PROVIDED BY THE DEVICES, filed Dec. 10, 2017, which is hereby incorporated by reference in its entirety as if fully set forth herein, including Specification, Figures, Claims, and all other matter.

FIELD OF THE DISCLOSURE

This disclosure relates generally to the field of smart traffic control devices, beacons for location services and the use of signals emanated by the beacons, and power train management in vehicles. Selected of the disclosed examples relate to fault monitoring and reporting by traffic control devices; to power train control of vehicles communicating with traffic control devices, including control of braking, accessory operation, and charging through regenerative braking; to speed management of vehicles communicating with traffic control devices; to vehicle position location techniques; to communications between smart traffic control devices and remote facilities; and to related vehicular and traffic control and management technologies.

BACKGROUND

A need in the art exists for improved vehicle power trains and techniques for managing vehicle power trains. A need in the art exists for improved traffic control devices and traffic control device fault monitoring and notifications. A need in the art exists for improved techniques for accurate estimation of locations of vehicles and other assets/things. A need in the art exits for improved communications with traffic control devices.

SUMMARY

This document describes embodiments, variants, implementations, and examples effectuating novel techniques for addressing one or more of the needs identified above, and/or other needs. Selected embodiments described in this document include methods, apparatus, and articles of manufacture that enable enhanced operations of smart traffic control devices, beacons, vehicle computers, vehicular power trains; and enhanced distance measurement and location estimation techniques.

In an embodiment, a traffic control device includes a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and bus(es) coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The processing module implements a state machine to control traffic, e.g., through the visual traffic control display(s). The processing module is configured to communicate with remote resource(s). The processing module and the remote resource(s) are configured to implement means for identifying false green request(s).

In an embodiment, a method of operating a traffic control device includes a number of steps. The traffic control device includes a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus (or buses) coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s), wherein the processing module is configured to communicate with a remote resource. The method steps include: operating a state machine controlling traffic, e.g., through the visual traffic control display(s); and step for identifying false green request(s).

In an embodiment, an article of manufacture includes at least one non-volatile machine-readable storage medium with program code stored in the at least one non-volatile machine-readable storage medium. When the program code is executed by (a) a processing module of a traffic control device that includes the processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s); and (b) one or more processors of a remote resource, the program code configures the processing module and the one or more processors to operate a state machine controlling traffic in the vicinity of the traffic control device; and to perform steps for identifying false green requests in the traffic control device.

In an embodiment, a traffic control device includes a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus (or buses) coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The processing module implements a state machine to control traffic. The processing module is also configured to communicate with a remote resource. The processing module and the remote resource are configured to implement means for detecting and verifying unidentified true green requests.

Another embodiment is a method of operating a traffic control device including a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus (or buses) coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state affecting sensor(s). The processing module is configured to communicate with a remote resource. The method includes: operating a state machine controlling traffic; and steps for detecting and verifying unidentified true green requests.

Another embodiment is an article of manufacture including at least one non-volatile machine-readable storage medium with program code stored in the at least one non-volatile machine-readable storage medium. When the program code is executed by (a) a processing module of a traffic control device that includes the processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and by (b) one or more processors of a remote resource, the program code configures the processing module and the one or more processors to operate a state machine controlling traffic in the vicinity of the traffic control device, and to perform step for detecting and verifying unidentified true green requests in the traffic control device.

In an embodiment, a traffic control device includes a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The processing module implements a state machine to control traffic. The processing module is configured to cause the traffic control device to implement means for communicating with a remote resource through vehicles passing in the vicinity of the traffic control device.

Another embodiment is a method of operating a traffic control device including a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The method includes operating a state machine controlling traffic; and step for communicating with a remote resource through vehicles passing in the vicinity of the traffic control device.

Another embodiment is an article of manufacture including at least one non-volatile machine-readable storage medium with program code stored in the at least one non-volatile machine-readable storage medium. When the program code is executed by (a) a processing module of a traffic control device including a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s), and by (b) one or more processors of a remote resource, the program code configures the traffic control device and the remote resource to operate a state machine controlling traffic in the vicinity of the traffic control device; and to perform step for communicating between the traffic control device and the remote resource through vehicles passing in the vicinity of the traffic control device.

In an embodiment, a traffic control device includes a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The processing module implements a state machine to control traffic in the vicinity of the traffic control device. The processing module is configured to cause the traffic control device to implement means for enabling vehicles and other devices in the vicinity of the traffic control device to estimate distance to the traffic control device by measuring phase shifts of at least three frequencies emitted by the traffic control device.

Another embodiment is a method of operating a traffic control device including a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The method includes operating a state machine to control traffic in the vicinity of the traffic control device; and step for enabling vehicles and other devices in the vicinity of the traffic control device to estimate distance to the traffic control device by measuring phase shifts of at least three frequencies emitted by the traffic control device.

Another embodiment is an article of manufacture including at least one non-volatile machine-readable storage medium with program code stored in the at least one non-volatile machine-readable storage medium. When the program code is executed by a processing module of a traffic control device including the processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s), the program code configures the traffic control device to perform steps including: operating a state machine to control traffic in the vicinity of the traffic control device; and step for enabling vehicles and other devices in the vicinity of the traffic control device to estimate distance to the traffic control device by measuring phase shifts of at least three frequencies emitted by the traffic control device.

In an embodiment, a traffic control device includes a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s). The processing module implements a state machine to control traffic in the vicinity of the traffic control device. The processing module is configured to cause the traffic control device to transmit in real time state(s) of the traffic control device in one or more directions of traffic movement controlled by the traffic control device. In variants, the processing module is further configured to cause the traffic control device to transmit in real time wait times to changes in the states. In variants, the processing module is configured to cause the traffic control device to transmit in real time indications of likelihood of the wait times to the changes in the states.

In an embodiment, a method of operating a traffic control device including a processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus or buses coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s) includes the following steps: implementing a state machine to control traffic in the vicinity of the traffic control device; and transmitting in real time state(s) of the traffic control device in one or more directions of traffic movement controlled by the traffic control device. In variants, the method further includes transmitting, in real time, wait times to changes in the states. In variants, the method further includes transmitting, in real time, indications of likelihood of the wait times to the changes in the states.

Another embodiment is an article of manufacture including at least one non-volatile machine-readable storage medium with program code stored in the at least one non-volatile machine-readable storage medium. When the program code is executed by a processing module of a traffic control device that includes the processing module, storage, camera(s), visual traffic control display(s), radio frequency transceiver(s), interface(s) to state-affecting sensor(s), and a bus coupling the processing module to the storage, the camera(s), the visual traffic control display(s), the radio frequency transceiver(s), and the interface(s) to the state-affecting sensor(s), the program code configures the traffic control device to: (a) implement a state machine to control traffic in vicinity of the traffic control device; and (b) transmit in real time states of the traffic control device in one or more directions of traffic movement controlled by the traffic control device. In variants, the program code further configures the traffic control device to transmit, in real time, wait times to changes in the states. In variants, the program code further configures the traffic control device to transmit, in real time, indications of likelihood of the wait times to the changes in the states.

In an embodiment, a traffic control device (TCD) includes: a processing module, storage, one or more cameras, one or more visual traffic control displays, one or more interfaces to state-affecting sensors, one or more remote interfaces to one or more remote computer systems, and one or more buses coupling the processing module to the storage, the one or more cameras, the one or more visual traffic control displays, the one or more interfaces to the state-affecting sensors, and the one or more remote interfaces.

The processing module is configured to: implement a state machine to control traffic through the one or more visual traffic control displays; obtain a preliminary false green request (FGR) detection; identify one or more locations that correspond to the preliminary FGR detection; obtain through the one or more cameras one or more recordings of the one or more locations, the one or more recordings corresponding to time a green request (GR) associated with the preliminary FGR detection was generated (first generated and/or continued to be generated); perform first machine-processing of GR-related data comprising the one or more recordings, to attempt to determine whether the preliminary FGR detection corresponds to a real GR; if the first machine-processing indicates that the preliminary FGR detection resulted from the real GR, clear the preliminary FGR detection (and resume or continue normal operation); if the first machine-processing does not indicate that the preliminary FGR detection resulted from the real GR, transmit through the one or more remote interfaces to the one or more remote computer systems information regarding events that caused the preliminary FGR detection, the information including at least some of the GR-related data, the at least some of the GR-related data including the one or more recordings; and clear the preliminary FGR detection (and resume or continue normal operation of the state machine), in response to receipt by the TCD of a clear signal from the one or more remote computer systems.

The one or more remote computer systems are configured to receive the information from the TCD; perform additional processing of the information to attempt to determine whether the preliminary FGR detection corresponds to the real GR or an FGR; and, if the additional processing indicates the preliminary FGR detection resulted from the real GR, transmit the clear signal to the TCD to cause the TCD to clear the preliminary FGR detection.

In aspects, a traffic management system includes the TCD, and the one or more remote computer systems. The processing module is further configured to adjust operation of the state machine to mitigate fault associated with the FGR (such as operate without regard to the reading of a state-affecting sensor found to be faulty), in response to receipt by the TCD of an adjust signal from the one or more remote computer systems. The one or more remote computer systems are further configured to transmit the adjust signal to the TCD to cause the TCD to adjust operation of the state machine to mitigate the fault associated with the FGR, if the additional processing indicates the preliminary FGR detection resulted from the FGR.

In aspects, the additional processing includes second machine-processing by the one or more remote computer systems.

In aspects, the additional processing includes engaging from the one or more remote computer systems one or more human resources to perform human processing.

In aspects, the additional processing includes engaging from the one or more remote computer systems one or more human resources to perform crowdsourced resource-processing.

In aspects, the one or more interfaces to state-affecting sensors include an interface to a pedestrian pushbutton.

In aspects, the processing module is further configured to perform the first machine-processing of the one or more recordings by searching the one or more recordings for presence of a pedestrian.

In aspects, the one or more interfaces to state-affecting sensors include an interface to a vehicle sensor (i.e., a sensor that senses presence of a vehicle).

In aspects, the one or more interfaces to state-affecting sensors include an interface to an inductive loop vehicle sensor, and the processing module is further configured to perform the first machine-processing of the one or more recordings by searching the one or more recordings for presence of a vehicle.

In aspects, the one or more remote computer systems are further configured to perform the additional processing by searching the one or more recordings for presence of a pedestrian or a vehicle.

In aspects, the one or more recordings include infrared recording(s) and/or ultraviolet recording(s).

In aspects, the one or more recordings include lidar output recording(s) and/or radar output recording(s).

In aspects, the TCD further includes a sound recording device, the processing module is further configured to make sound recordings corresponding to the time the GR associated with the preliminary FGR detection was generated, and the at least some of the GR-related data further includes the sound recordings.

In aspects, the TCD includes one or more radio frequency receivers and one or more radio frequency transmitters, and the processing module is further configured to connect through the one or more radio frequency receivers and the one or more radio frequency transmitters to mobile devices in the vicinity of the TCD to obtain additional recordings of the one or more locations, and the at least some of the GR-related data comprises the additional recordings.

In aspects, the TCD includes one or more radio frequency receivers and one or more radio frequency transmitters, and the TCD and the one or more remote computer systems are further configured to implement the one or more remote interfaces to include means for communication between the TCD and the one or more remote computer systems via vehicles and/or mobile devices passing in the vicinity of the TCD.

In aspects, the TCD and the one or more remote computer systems are further configured to implement means for detecting and verifying unidentified true green requests.

In aspects, the TCD includes a radio frequency transmitter (which may but need not be part of the one or more remote interfaces), and the TCD is further configured to implement beacon means for facilitating distance measurement between a point (e.g., in the vicinity of the TCD) and the TCD using transmissions of a radio frequency carrier modulated with at least three low frequencies and measurement of at least two phase differences of the at least three low frequencies at the point.

In aspects, an apparatus includes a TCD and a vehicle computer. The vehicle computer includes a processor and a vehicle radio frequency receiver that enables the vehicle computer to receive the transmissions of the radio frequency carrier modulated with the at least three low frequencies and measure the at least two phase differences between of the at least three low frequencies. The processor implements means for measuring distance to the TCD based on the at least two phase differences.

In aspects, the TCD further includes a radio frequency transmitter coupled to the processing module by the one or more buses; and the processing module is further configured to cause the TCD to transmit in real time through the radio frequency transmitter state information describing current state of the one or more visual traffic control displays and time to changes in the state of the one or more visual traffic control displays. A vehicle power train control system may include the traffic management system and a vehicle computer configured to control power train functions of a vehicle. The vehicle computer includes a processor and a vehicle radio frequency receiver that enables the vehicle computer to receive the state information and the time to changes in the state, and to vary operation of power train of the vehicle in response to changes in the state and/or changes in the time to changes in the state.

Various features and aspects will be better understood with reference to the following description, drawings, and appended claims.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 illustrates selected components of a traffic control device configured in accordance with selected features described in this document;

FIG. 2 illustrates selected steps/decision blocks of a process for identifying faults in traffic control devices and/or in sensors connected to the traffic control devices;

FIG. 3 illustrates selected steps of another process for identifying faults in traffic control devices and/or in sensors connected to the traffic control devices;

FIG. 4A illustrates selected steps of a process for transmitting signals that facilitate distance measurement;

FIG. 4B illustrates selected steps of another process for transmitting signals that facilitate distance measurement; and

FIG. 5 illustrates selected steps of a process for receiving beacon signals and estimating distance between a receiving device and a beacon.

DETAILED DESCRIPTION

The words “embodiment,” “variant,” “example,” “implementation,” and similar words and expressions as used in this document refer to a particular apparatus, process, or article of manufacture, and not necessarily to the same apparatus, process, or article of manufacture. Thus, “one embodiment” (or a similar word/expression) used in one place or context may refer to a particular apparatus, process, or article of manufacture; the same or a similar expression in a different place or context may refer to a different apparatus, process, or article of manufacture. The expression “alternative embodiment” and similar words and phrases are used to indicate one of a number of different possible embodiments, variants, or examples. The number of possible embodiments, variants, or examples is not necessarily limited to two or any other quantity. Characterization of an item as “exemplary” means that the item is used as an example. Such characterization does not necessarily mean that the embodiment, variant, implementation, or example is a preferred one; the embodiment, variant, implementation, or example may but need not be a currently-preferred embodiment, variant, implementation, or example. All embodiments, variants, implementations, and examples are described for illustration purposes and are not necessarily strictly limiting.

The words “couple,” “connect,” and similar words/phrases/expressions with their inflectional morphemes do not necessarily import an immediate or direct connection, but include within their meaning connections through mediate elements. Unless otherwise noted or is clear from the context, devices may be coupled/connected wirelessly, optically, and in a conventional wired manner.

The expression “processing logic” should be understood as selected steps/decision blocks and/or hardware/software/firmware for implementing the selected steps/decision blocks. “Decision block” means a step in which a decision is made based on some condition, and subsequent process flow is directed based on whether the condition is met or not met.

Two or more directions controlled by a traffic control device are “conflicting” when the traffic control device may not safely allow traffic, whether pedestrian or vehicular, to flow in the two or more directions at the same time. Suppose, for example, that the traffic control device controls a four-way intersection (no overpasses) with North-to-South, South-to-North, East-to-West, and West-to-East traffic flows. The North-to-South vehicular traffic flow need not conflict with the South-to-North traffic flow, but will conflict with both East-to-West and West-to-East traffic flows. Additionally, the North-to-South vehicular traffic flow may conflict with vehicular traffic approaching from South and waiting to make a left turn towards West; and with pedestrian traffic waiting to cross the North-South roadway. These are of course merely examples, and conflict between and among different directions may be programmed differently, for example, showing a red “DO NOT CROSS” or “DO NOT WALK” or “STOP” display to prohibit pedestrians from crossing in any direction when any vehicular traffic is allowed (by a green light, for example) through the intersection in any direction. Similarly, right turn may be allowed (perhaps after a stop) from a lane that may not cross the intersection. It is a matter of design of the intersection and choice of operating procedures programmed into the state machine of the traffic control device, which, of course, should not be nonsensical in the real world.

A “green request” or “GR” informs a traffic control device (“TCD”) that some entity (e.g., a pedestrian, a vehicle) needs to proceed in a particular direction (and consequently to prevent flow of traffic in the conflicting directions). For example, detection of a vehicle in a particular lane is a GR to proceed in a particular direction that is associated with the lane, such as proceed forward, proceed with a left turn, or proceed with a right turn. As another example, activation of (pressure on) a pedestrian crossing pushbutton is a GR to change the state of a pedestrian control display to WALK (or equivalent display) in the direction associated with the pushbutton (i.e., the direction in which the pedestrian signals that he or she wishes to proceed/cross). An unambiguous GR indicates traffic (whether vehicular or pedestrian) proceeding or waiting to proceed in a particular direction. An inductive loop signal indicating a vehicle in a center lane of an intersection where turns from the center lane are prohibited is an unambiguous GR; an inductive loop signal indicating a vehicle in a right (or left) lane of an intersection where turns from the right (or left) lane are allowed but not required is an ambiguous GR, because the vehicle may proceed forward or turn; an inductive loop signal indicating a vehicle in a center lane of an intersection where right turns from the center lane are allowed is also an ambiguous GR; receipt of an emergency preemption signals may be ambiguous or unambiguous, depending on the details (whether direction is indicated) provided by such signals and the treatment of such signals by the TCD. Often, however, an emergency preemption signal is an unambiguous green request, telling the traffic control device to disallow traffic in all directions; no green light need be associated with an emergency preemption signal, because emergency traffic with a siren may be able to proceed lawfully against a red light.

A malfunction causing a continuous (or periodic, or even merely occasional) reporting of a request for a permission to proceed in a given direction without actual traffic (whether vehicular or pedestrian) causing the request is a “false green request” or “FGR.” Examples of false green requests include: a stuck pushbutton of a pedestrian crossing and an inductive loop sensor malfunction that produces an unwarranted vehicle detected signal (such as a continuous vehicle detected signal); a proper vehicle detected signal due to a vehicle that stays near an inductive loop for a prolonged time (such as an illegally parked vehicle, broken down vehicle, maintenance vehicle for work in the immediate vicinity of the TCD, etc.) is also an FGR cause, though the “malfunction” here exists in the sense of an irregular condition that appears to indicate a need for some corrective action. Other examples include emergency preemption request signals (as explained above) sent from malfunctioning or maliciously operated emergency vehicle operator devices or from other devices that create interference mistaken by the TCD for emergency preemption request signals, and otherwise improperly arisen/detected emergency preemption signals.

Thus, false green requests may be generated by a temporary condition that is expected to clear by itself, such as an improperly parked or a disabled vehicle, or a maintenance work vehicle parked in a traffic lane; such false green requests are “soft.” False green requests may also be generated by a device malfunction that is not expected to clear by itself, at least not within a reasonable or foreseeable time, such as a malfunction of a sensor (e.g., pushbutton, inductive loop), malfunction in the TCD itself (e.g., bad operation of one of the interfaces to external devices/sensors or other hardware/software failures of the TCD). Such false green requests are “hard.” Additionally, false green requests may also be of unknown origin or otherwise not being easily susceptible to classification as to the ability to clear by themselves within a reasonable time (e.g., under one, two, three, four, five days, or even several weeks or months). These include radio interference, including malfunctions in, or abuse of, emergency preemption request signal-generating devices. Such false green requests are “unknown” false green requests.

A false green request may be re-classified based on changing circumstances. For example, a stuck pushbutton may become unstuck and the false green request may clear. Similarly, radio interference may disappear or abate, and the initially-resulting unknown false green request may then also clear. As another example, an abandoned vehicle may initially result in a soft false green request, but after a predetermined period of time may be re-classified as either unknown or hard false green request.

Another type of malfunction causes a legitimate request for a permission to proceed in a given direction (a “true green request” or “TGR”) not to be reported to the TCD. For example, a pushbutton or an inductive loop malfunction can result in a TGR that is not reported to the TCD or otherwise not detected by the processing module (that operates the state machine) of the TCD. Such TGR may be referred to as “undetected” TGR or “UTGR.” Another example of a UTGR cause is a malfunction in an interface of the TCD to external sensors, such as interfaces to pedestrian pushbuttons and inductive loops.

A “vicinity of a traffic control device” and analogous expressions signify the area within which the traffic control device controls traffic. Roadway and pedestrian walkways within 25 meters of a TCD and leading to or away from the TCD would typically be in the vicinity of the TCD. In the contexts of (a) transmitting traffic signal state information and expected change in the state, and (b) distance measurement, the “vicinity” includes areas within reach of short and medium range communications of transceivers 120A/B described below.

In a number of places, this disclosure refers to “video” and “still” images. Video and still images may be in the visible portion of the electromagnetic spectrum, infrared portion of the spectrum, ultraviolet portion of the spectrum, or any combination thereof, whether or not specifically mentioned in context. Of course, the description and claims may specifically refer to a particular part or parts of the spectrum, and in the context of such references, the images are in the specific part or parts of the spectrum.

A server or a facility or a computer system is “remote” to another item (such as a TCD/beacon) in the physical sense. The remote server/facility/computer system is not collocated with the item, as in the same enclosure or building. Typically, “remote” indicates a distance of at least one mile (0.6 km), but may be ten or more miles, possibly more than 100 miles and even more than 1000 miles. As will be made clear, a remote server/facility/computer system typically has processing resources additional to, and/or of a character different from, the resources of the item. The additional processing resources may include human resource(s), which may be crowdsourced resources, and an interface to such human/crowdsourced resources.

Some definitions have been explicitly provided above. Other and further explicit and implicit definitions and clarifications of definitions may be found throughout this document.

FIG. 1 illustrates selected components of a traffic control device or TCD 100 that may be configured in accordance with one or more features described in this document. The TCD 100 may be, for example, a traffic light. The TCD 100 includes a processing module 105. The TCD 100 also includes storage device(s) 110 (which may store program code for execution by the processing module 105, other program code, various data mentioned in this document, scratchpad data, as well as other data and code). The TCD 100 additionally includes one or more radio frequency (RF) receivers 120A and transmitters 120B. The RF receivers 120A may be configured to receive radio frequency signals; the RF transmitters 120B may be configured to transmit radio frequency signals; each RF receiver 120A and/or transmitter 120B may include its own processing module in addition to the processing module 105, and be controlled by its own processing module and/or by the processing module 105. The TCD 100 further includes one or more RF transmit and receive antennae 125 coupled to the receivers/transmitters 120A/120B; in embodiments, there is a single antenna that serves both to receive and transmit RF signals; in embodiments, there are several receive and transmit antennae. The TCD 100 further includes still and/or video camera(s) 130. The TCD 100 further includes one or more visual traffic control displays (“VTCDs”) 135. The TCD 100 further includes one or more interfaces 140 to state-affecting sensors, i.e., sensors that may affect the state of the TCD 100. The TCD 100 further includes one or more buses 145 that couple(s) the processing module 105 to some or all of the other components of the TCD 100, allowing the processing module 105 to read from and write to these devices, and/or otherwise to control operation of some or all of these devices. In embodiments, one or more additional buses interconnect the components (other than the processing module 105) directly, for example, for direct memory access of one of the other devices by another device of the TCD 100.

In embodiments, the TCD 100 includes additional components, such as an additional device 142, which components may be coupled to the processing module 105 through the bus(es) 145 or otherwise.

The processing module 105 may include, for example, one or more processors, such as microprocessors, dedicated processors, microcontrollers, and field-programmable devices (field-programmable gate arrays and similar field-configurable devices), and their supporting circuitry, such as DRAMs and other memories, with their controllers.

The storage device(s) 110 may include one or more Read Only Memories (ROMs), one or more Electrically Programmable ROMs (EPROMs), one or more Electrically Erasable Programmable ROMs (EEPROMs), magnetic storage devices (e.g., hard disk(s)), optical storage devices (e.g., CD-ROMs, DVD-ROMs), flash memories, and other forms of volatile and non-volatile storage media. Non-volatile storage media may include volatile memory with battery back-up.

The RF receivers 120A and transmitters 120B may include cellular radio receivers and transmitters that enable the TCD 100 to communicate with other devices such as cellular networks and through them with smart cell phones and applications (apps) running on the cell phones, the Internet, and other Internet-connected devices. The RF receivers 120A and transmitters 120B may include long-range RF receivers and transmitters that can communicate with vehicle computers in vehicles, smart phones, other mobile devices, and other TCDs, over distances up to and over 100 meters. The RF receivers 120A and transmitters 1201B may include medium range and short range RF receivers and transmitters that can communicate with vehicle computers in vehicles, smart phones, other mobile devices, and other devices in distances up to about 100 meters in normal operation. The RF receivers 120A and transmitters 120B may include Bluetooth® devices and other devices with the same or substantially same range. One or more of the RF transmitters 120B may also emit beacon signals, which may but need not additionally carry payload information and location information such as coordinates of the TCD and TCD state information and time to change of state information, and serve for location and distance measurement of devices such as vehicles and portable communication devices such as smart phones, tablets, gaming devices, dedicated navigation devices, computers, and devices designed for distance measurement/location services.

The RF antennae 125 may be omnidirectional and substantially omnidirectional, horizontally-omnidirectional and substantially horizontally-omnidirectional; the antennae 125 may also be directional, including directional in the horizontal plane (transmitting in a predetermined or adjustable azimuthal (compass) direction over a range of altitude/elevation angles). The antennae 125 may include one or more antennae for operation on various frequencies. A single antenna may be used for receiving and transmitting on the same frequency, on multiple frequencies, and in a range of frequencies.

The one or more cameras 130 may capture still pictures and videos, in the visible light, infrared portions of the spectrum, and/or ultraviolet portions of the spectrum. The cameras 130 may be stereoscopic. The camera(s) 130 may be wide-angle, e.g., with over 90 degrees of coverage. In embodiments, the cameras 130 face different directions; their horizontal coverage may overlap, and may extend horizontally 360 degrees. In embodiments, the camera(s) 130 may be configured to determine distances from the TCD 100 to various objects, including distances to stationary objects such as vehicles; this may be done as is known in the art of photographic and video imaging and focusing. The cameras 130 may include foveated vision/imaging capabilities.

The visual traffic control display or displays 135 may include conventional red-yellow-green (“RYG”) traffic lights and symbols facing one or multiple directions. The VTCDs 135 may include directional arrows in various colors (e.g., RYG), for controlling turning traffic, and various alphanumeric indicators, such as “STOP,” WALK,” and “DO NOT WALK” in various colors, for pedestrians and/or drivers, which arrows and/or symbols may face one or multiple directions. The VTCD(s) 135 may be intended to control vehicular traffic, pedestrian traffic, or both.

The interfaces 140 may include inputs from external devices that affect the state of the TCD 100 as the state relates to immediate or future changes of the display signals produced by the VTCD(s) 135 under control of the processing module 105. (Or, more precisely, potentially affect the state of the TCD 100, depending on the state of the TCD 100 and the inputs from the external devices.) The inputs may read/sense the states of a number (one or more) of inductive loop traffic detectors, for example, inductive loop traffic detectors buried under the roadway surface; pedestrian crossing pushbutton(s) and analogously-purposed devices such as devices designed to receive pedestrian traffic requests from smart phones and other mobile devices including devices built into wheelchairs, whether directly through short range RF and other transmissions, or by way of a cellular service; inputs from traffic signal interruption device signals, for example, signals from emergency vehicle operator devices designed to interrupt regular operation of traffic control devices (including the TCD 100) and give priority to the emergency vehicles (“emergency preemption signals,” which have already been mentioned); traffic sensing radar and/or other traffic sensing RF devices, whether active or passive; traffic sensing lidar and/or other traffic sensing active devices operating in the visible, infrared, and/or ultraviolet portions of the electromagnetic spectrum; and passive optical traffic sensing devices, such as cameras with image processing capability (which capability may be provided by built-in processors, separate processors, and/or the processing module 105); and inputs from other devices that may affect the state of the TCD 100 immediately or in near future, such as within 30 seconds, within 1 minute, within 2 minutes, within 3 minutes, within 4 minutes, and within 5 minutes. The nature of each interface 140 depends on its corresponding sensor. For example, an input may be simply a wire or a pair of wires that may convey information through the voltage on the wire or across the pair, or resistance between the wire inputs, or otherwise. The voltage may be controlled, e.g., by a pedestrian crossing pushbutton; by an inductive loop; by a self-contained sensor of the type mentioned above or another type, or otherwise. Additionally or instead, the interfaces 140 may provide for receiving (or exchanging) data that is not simply binary on-off. For example, a radar/lidar/photo appearance/signature or image may be received through an interface 140 for processing by the processing module 105 or otherwise; similarly, various digital signals may be received through the interfaces 140.

It should be noted that signals affecting the state of the TCD 100 may also or instead be received from other components of the TCD 100, including those described above. Thus, emergency preemption signals may be received, for example, through the RF receiver(s) 120A. Similarly, photo/video data may be received from the camera(s) 130. Again, these are non-exclusive examples.

The bus(es) 145 may be of any design, including conventional serial and parallel bus designs for internal computer communications. Additionally, in the present context, “bus”/“buses”/“buss”/“busses” also designate direct connections between and among devices (components of the TCD 100) to allow unidirectional or multi-directional (two or more) flow of information and control and other signals between and/or among the devices. These connections may be, for example, electrically wired, optical, or wireless.

The operation of the VTCD(s) 135 may be controlled by a state machine, for example, a state machine implemented by code executed by the processing module 105. As a person skilled in the art would understand after careful perusal of this document, the states (and their corresponding displays of the VTCD(s) 135) and state transitions may be affected by the signals/information received through the interfaces 140, the RF receivers 120A, the camera(s) 130, internal timers, and possibly other internal/external devices.

As has already been discussed in the context of defining FGRs, the sources of the state-affecting signals may malfunction or otherwise send corrupted signals to the processor module 105, through the interfaces 140 or otherwise. For example, a pushbutton of a pedestrian crossing may be stuck in the pushed-in position; an inductive loop may constantly produce a signal corresponding to a vehicle awaiting a light change, regardless of the presence of such vehicles; signal corruption in this sense may also result from a vehicle that is on top or near (within sensing distance of) the inductive loop, perhaps, for example, because the vehicle broke down, is illegally parked, or is an emergency/maintenance vehicle stopped in a traffic lane. The corrupted signals received by the processing module 105 can cause the state machine to operate so that the flow of traffic at the intersection is deleteriously affected. For example, the TCD 100 may lengthen green light in one direction in response to the corrupt signal erroneously indicating that there are cars still flowing in this direction; the traffic (vehicular/pedestrian) flow in one or more conflicting directions may then be deleteriously affected.

In embodiments, the processing module 105 of the TCD 100 executes code to detect corruption of the state-affecting signals/information received through the interfaces 140 or otherwise. Upon detection of the corruption of the signals/information, the processing module 105 may execute code to adjust the operation of the TCD 100 to reduce or eliminate the deleterious effect of the corruption; the processing module may also or instead execute code to report a malfunction, for example, report the malfunction to a proper authority, or for additional processing/verification/evaluation at one or more remote facilities. The additional processing/verification/evaluation may include the use of human resources, including crowdsourced resources and persons outside of the jurisdiction (state, country) where the TCD 100 in located.

There are several ways to detect FGRs and UTGRs. The process of detecting FGRs and UTGRs may be broken into two parts: (1) preliminary detection, and (2) verification (confirmation/disconfirmation). Preliminary detection may be performed by comparing recent state changes (including the absence of state changes) of a given green request. For example, if a particular GR has been continuously signaled for over a predetermined period of time, a preliminary detection of an FGR may be made. Similarly, if a particular GR has not been detected for a predetermined period, a preliminary detection of a UTGR may be made. The lengths of the predetermined periods (for FGR and/or UTGR preliminary detection) may be a function of various variables, including time of day, day of the week, calendar date. In particular, the following day/date/time attributes may affect the lengths of the predetermined periods: whether it is a work/business day, a weekend day, a school day, a holiday (federal, state, religious), significant traffic-affecting event day in general or within a predetermined distance (e.g., a local fair or farmers' market, a parade, a presidential/dignitary visit, within one, two, three miles of the TCD, day time, night time, rush hour or business hours (such as 9 am-6 pm). The length of the predetermined period may be initially set to some default value and then changed based on the statistics of actual traffic and GRs detected at the TCD or on other TCDs in a larger area. Additionally, a preliminary detection of an FGR may be made when the particular GR is not continuously signaled but nevertheless is signaled for a percentage of time that is much greater (e.g., ×2, ×3, ×10) than would be expected, based on the other factors (e.g., day/date/time etc.). Multifactor, regression, principal component, and other statistical techniques may be employed to determine the influence of the different factors on the length of the expected changes in the GRs and deviations from the expected changes in GRs. Neural networks including deep learning, and other artificial intelligence (“AI”) systems, may also be employed, based on the experience of other TCDs and their malfunction reporting; the other TCDs may be in similar (from e.g., traffic flow perspective and/or population density perspective) locations. The variables/parameters input into the AI algorithms for learning may include population density near the TCDs, traffic flow in the vicinity of TCDs, distance to known/visible security cameras, distance to law enforcement bases (police/sheriff stations), and others.

The verification step may be performed in several ways, some or all which may be combined. (As is generally the case with all features described throughout this document, which may be present individually, in any combination, and in any permutation.) FIG. 2 illustrates steps of a process 200 for verifying a preliminary detection of an FGR. At flow point 201, the TCD 100 and other devices (if applicable) is (or are, as the case may be) powered-up, initialized, and ready to perform the steps of the process 200.

In step 205, a preliminary detection of an FGR is obtained. The preliminary detection may be generated by the TCD 100, received by the TCD 100 from elsewhere, received by a remote processing device (or devices) such as a remote server and sent to the TCD 100, and/or generated by the remote device(s) based on the information provided by the TCD 100 and/or other sources. Some examples of preliminary FGR detections have already been described: continuous or prolonged or frequent GR(s).

In step 210, the physical locations corresponding to the preliminary detection are identified. Physical locations that correspond to the preliminary detection are such locations from which a true GR associated with the FGR may be generated. If the GR relates to a pedestrian crossing pushbutton, for example, the physical locations are locations where persons who pressed the pushbutton would have been located (e.g., within an arm's reach, less than 1, 2, 3, 4, or 5 meters of the pushbutton) at the time the pushbutton was pressed and within some short period (e.g., less than 1, 2, 3 seconds) of the time the pushbutton was pressed. If the GR relates to an inductive loop sensor, the physical locations are locations where a vehicle that activated the inductive loop sensor would have been located at the time the sensor was activated and within some short period (less than 1, 2, 3, 4, or 5 seconds) within the time the sensor was activated (e.g., less than 3, 5, or 10 meters of the inductive loop). All such locations may be identified, for example, through a pre-stored mapping of sensors to the corresponding locations. If the GR relates to multiple inputs/sensors (e.g., pedestrian pushbuttons on opposite sides of a roadway that produce inputs that the TCD cannot distinguish, different inductive loops on the same input), then all such locations for each of the inputs/sensors may be identified.

Still and/or video recordings of these locations at the time (and possibly slightly before and/or if applicable after the time, as is discussed below) the GR (the preliminary detection of the FGR) was generated are obtained, in step 215, so that they can be examined. For example, the TCD 100 identifies such recordings based on the camera(s) 130 locations and directions in which they face (the cameras' orientations), and the relevant time period(s); as another example, the TCD 100 requests the recordings from one or more external cameras, basing the request(s) on the time of the GR and the identified physical locations. The external cameras may be not part of the TCD 100 but nevertheless available to (accessible by) the TCD 100; they may be stationary or mobile, and may be installed in mobile devices (such as smart phones, tablets, PCs) and vehicles of persons in the vicinity of the TCD 100 at the time of the GR. Additionally, sound recordings, lidar output recordings, and radar (and, more generally, active/passive RF device) recordings corresponding to the same timeframe may be obtained in this step. The camera(s) 130 and/or the external cameras may use foveated vision/imaging capabilities to obtain better images of particular locations.

In step 220, the still and/or video and/or other recordings corresponding to the time the GR was generated (e.g., within 50 milliseconds, 100 milliseconds, 500 milliseconds, 1 second of the time the GR was first generated or continued to be generated) are initially examined automatically (machine- or computer-examined), to determine whether an appropriate entity (e.g., a person in the case of a pushbutton GR, a vehicle in the case of an inductive loop sensor GR) was present in the location(s) at the time of activation/detection. The presence of a person near (e.g., within an arm's reach of, within 3 feet of) the pushbutton at the time would strongly suggest that the person pressed the pushbutton and the GR was not a false one; and a vehicle in the immediate proximity of the inductive loop sensor (e.g., within the known maximum or typical sensory range of the inductive loop) would strongly suggest or even conclusively establish that the GR was not a false GR. The automatic examination may include attempting to recognize a vehicle (even a small one, such as a bicycle) or another large object in the locations by the visual/IR/UV appearance/signature of the vehicle/object, by its radar/lidar appearance/signature, appearance/signature of another type of RF reflections, by its sound signature. The TCD 100 may store (e.g., the processing module 105 storing in the storage 110) a variety of signatures (whether visual/IR/UV signatures, radar/lidar signatures, other types of RF reflection signatures, sound signatures) and their correspondence or probability of correspondence to actual objects/vehicles/persons. The automatic examination may include comparing the current signature (of whatever kind) to the stored signatures, and determining that a person (or a vehicle) was present in the location(s) based on the match (beyond a predetermined probabilistic level). Artificial Intelligence algorithms may be employed for this purpose and, as will be seen, the AI algorithms may be improved based on the processing in the remote facilities, particularly human processing and crowdsourced processing.

If the result of the automatic examination in the step 220 is conclusive or suggesting strongly (“COSS”) that the GR was a real one and not an FGR, as determined in decision block 225 based on the automatic examination in the step 220, process flow continues to step 230. The step 230 clears the preliminary detection, returning the TCD 100 to normal operation. Supplemental processing may also be performed, as well as storage of the information (sensor readings, video/still/other recordings) that resulted in or is associated with (e.g., same timeframe) the preliminary detection in the step 205. The process 200 may then end at flow point 299. The process 200 may be repeated as needed or desired, for example, caused by another preliminary FGR detection in the step 205.

A result is a COSS GR result when the step 220 indicates with sufficient certainty (such as a probability greater or no less than a predetermined threshold) that the GR was real; the predetermined threshold may be between 50% and 100%, but other threshold values may also be used. When the step 220 is designed to indicate either of two possibilities (1) a GR, or (2) not a GR, only the first indication (GR) is a COSS GR result. When the step 220 is designed to indicate one of three or more possibilities (1) GR, (2) uncertain (there may be a number of possibilities here, with different probability ranges), and (3) not GR, then only the first possibility (GR) may be considered a COSS GR result in some embodiments; in other embodiments, the “uncertain” possibility or some of the “uncertain” possibilities are also considered COSS GR. When the result of the step 220 is designed to produce a range of possibilities between a certain GR and a certain not GR, then a COSS GR result applies only to all the possibilities indicating GR at or above the predetermined level, such as the predetermined threshold of 50%-100% probability and above. In embodiments, recognition of a person in the relevant location and relevant timeframe is considered a COSS pedestrian pushbutton GR; and recognition of a large object (the size of a vehicle, possibly even a relatively-small one such as a bicycle, and/or an object with a sufficiently strong electromagnetic and/or optical signature) within the maximum or typical sensory range of an inductive loop is considered a COSS inductive loop GR.

If the result of the automatic examination of the step 220 is not conclusive/strongly suggestive that the GR was real (not a “COSS GR” as determined in the decision block 225), process flow continues to step 240, to transmit the information regarding the events that caused generation of the preliminary detection of the FGR from the TCD 100 to one or more remote processing facilities, e.g., the remote servers (or server, as the case may be here and throughout this document). If the TCD 100 itself generated or received the preliminary detection of the FGR from elsewhere, the TCD 100 may transmit to the remote facility(ies) the information that caused the generation by the TCD 100 of the preliminary detection (such as information received through the interfaces 140, video/still/other recordings received from the camera(s) 130, information received from another device, and identification of the corresponding locations and times). The information transmitted to the remote facility(ies) may include the number of times the sensor inputs received by the TCD 100 through the interfaces 140 transitioned and the direction of the transitions, and/or images/videos generated by the still and/or video camera(s) 130, during the times near and preferably surrounding the time the preliminary indication was generated. The TCD 100 may also or instead transmit radar and/or lidar and/or sound and/or other RF signal-based recordings of the objects detected near the vehicle and/or pedestrian sensors. The TCD 100 thus may have the capability to make such recordings, for example, including microphone(s) to capture sound, receivers and/or illuminators in the visual/IR/UV and RF portions of the spectrum, and other devices. The TCD 100 may transmit the information to the remote facility(ies) using the transmitters 120B, or other communication interface(s) of the TCD 100. For example, the TCD 100 may have wiring (e.g., wire lines, optical connections), connecting it to a network and/or to one of the remote facilities.

While waiting for a decision regarding the preliminary detection of the FGR (whether it resulted from a real GR or a fault) from the remote facility(ies), the TCD 100 may adjust the operation of the state machine, in effect presuming for the time being that the preliminary FGR detection resulted from a fault.

In embodiments, the TCD 100 records and stores the video continuously and/or still images continually (periodically and frequently), as well as the states of the sensors connected through the interfaces 140 and the radar/lidar output data. The recording may be on a looped basis, for example, a loop of 1-10 seconds, less than 30 seconds, less than 1 minute, less than 5 minutes, less than 10 minutes, or another duration; and when some earlier time information is needed (e.g., to analyze in the step 220 and/or to send to the remote facility in the step 240), the overwriting of the looped recording may be stopped and the recording for the relevant period may be retrieved and analyzed/sent. The following patent documents describe somewhat similar schemes for looped recording: Yoshizaki et al., U.S. Pat. No. 8,870,365 (“Yoshizaki”); and Fiedler, U.S. Pat. No. 6,804,638 (“Fiedler”). The disclosures of Yoshizaki and Fiedler are incorporated herein by reference in their entireties. In sum, the recorded information (sensor states, visible/IR/UV video, visible/IR/UV still images, radar/lidar output data) is retrieved for a period that may begin before the preliminary indication of an FGR is generated or received, and before the time that the event that resulted in the preliminary indication of the FGR occurred or was sensed/detected; and may extend until after the preliminary indication of an FGR is generated or received, and after the time that the event that resulted in the preliminary indication of the FGR occurred or was sensed/detected. The total duration of the retrieved and analyzed/sent recording may be preset and may be sufficiently long to determine with high likelihood of accuracy whether the GR was real or false, in typical circumstances; for example, the duration may be between 1 and 10 seconds, though shorter durations may suffice and longer durations may be useful.

In embodiments, another device such as a video or still camera installed or otherwise available in the vicinity of the TCD 100 or a video/still camera of a smart user device (such as a smartphone) in a vehicle in the vicinity of the TCD 100 records and stores the visible/IR/UV video continuously and/or visible/IR/UV still images continually at predetermined intervals (for example, every one-half second, every second, every 2 seconds), and provides/transmits the recorded information in the same or analogous manner, in the step 240, to the remote facility(ies), directly, through the TCD 100, and/or through other devices. The recordings from the other device(s) may be opportunistic and obtained by the TCD 100 via an interrogation request to the other device(s).

Once the information from the step 240 is received at the remote facility (or facilities, as the case may be), in step 245, it may be processed more extensively there, using additional and/or other resources, in step 250. These additional/other resources may include computational resources, data base resources, and algorithmic resources (“automated resources”). For example, at the remote facility(ies) (1) additional information regarding traffic flows may be available (such as from additional cameras, stationary or in-vehicle and other mobile cameras), and/or (2) more extensive computational resources may be available, and/or (3) better or different artificial intelligence algorithms may be available. (Here as in the step 220, AI algorithms may be employed and, as will be seen, the AI algorithms may be improved based on the processing in the remote facilities, particularly human processing and crowdsourced processing.) The result of the step 250 may also be (1) conclusive or strongly suggesting that the GR was a real one and not an FGR, or (2) other; this is determined in decision block 255.

If the result of the automatic examination of the step 250 (which is similar/analogous to the step 220, though it may use additional automated resources and/or additional information) is conclusive or strongly suggestive of a real GR (e.g., showing that a person was next to or within a predetermined distance of the pushbutton, or a vehicle was in immediate proximity of the inductive loop sensor, such as within the inductive loop's maximum or typical sensing distance), as determined in decision block 255, a transmission from the remote facility to the TCD 100 may be made, in step 260.

(The determination performed in the decision block 255 may be similar to, analogous to, or same as the determination performed in the decision block 225, though the input into the decision block 255 may include data other than the data input into the decision block 225.)

The transmission in the step 260 is received at the TCD 100, causing the TCD 100 to clear the preliminary detection of the FGR, so that the TCD 100 may continue operating normally. The process may then terminate at the flow point 299. The process may be repeated as needed or desired.

If, however, the result is not conclusive or strongly suggestive of a real GR, as determined in the decision block 255, the remote facility may engage one or more human resources, in step 265, to make a final determination (in the context of the process 200) regarding the need to clear the preliminary FGR detection, so that the TCD 100 may continue operating normally, and the need to take corrective action and adjust the operation of the TCD 100. For example, the relevant information (such as the visible/IR/UV still images, visible/IR/UV video, log of events received through the interfaces 140) may be sent to one or more human analyzers specially trained to make an appropriate determination based on such information, and/or to untrained human analyzer(s).

In embodiments, the human resources is/are or include crowdsourced or crowdsourcing resource(s). The Amazon Mechanical Turk is an example of a crowdsourcing Internet-based resource that enables the use of human intelligence for tasks that computers do not yet perform well. Requesters post tasks that providers can perform for compensation. Thus, in the step 265, a crowdsourced human resource may be engaged, for example, automatically assigning the determination to a predetermined number (one or more) of pre-qualified providers, and measuring their consensus. A consensus above a predetermined percentage is assumed to be conclusive as to the GR being real or false. The predetermined percentage may vary based on the number of providers. Note, however, that a single provider may be used, and the single provider's determination may be conclusive.

The human analyzer (which may include several humans and a computer system for aggregating their responses) may then provide an answer to decision block 270. If the human analyzer considers that the GR event was real (not an FGR), process flow continues to the step 260, to transmit to the TCD 100), causing the TCD 100 to clear the preliminary indication so that the TCD 100 may continue operating normally. The process then terminates at the flow point 299, and the process may be repeated as needed or desired.

If the human analyzer decides that the event is (or is likely to be) an FGR, process flow continues to step 275, to log (record) the FGR and the related information, such as the sensor inputs, video/still/sound recordings, relevant times and locations. This may also be performed at the remote facility(ies).

In step 280, which follows the step 275, a transmission is made from the remote facility to the TCD 100, to notify the TCD 100 that an appropriate adjustment to the operation of the state machine of the TCD 100 should be made. For example, the TCD 100 may, in response to this “adjust” notification, stop relying on a particular faulty input, and switch to default (e.g., timed) transitions of the state machine, in part or in whole. In embodiments, the needed adjustment may already have been made by the TCD (when the TCD in effect presumed for the time being that the preliminary FGR detection resulted from a fault), so the effect of the notification may be for the TCD to continue operating in the same adjusted manner.

In step 285, the TCD 100 receives the “adjust” notification, and performs the appropriate adjustment(s) (or continues to operate as previously adjusted). The notification may indicate the specific adjustment(s) needed, or notify the TCD 100 of the specific fault, or simply confirm the FGR corresponding to the preliminary detection obtained in the step 205. In embodiments, the “adjust” notification includes an identifier of the transmission of the steps 240/245, or an identifier of the preliminary detection of the step 205, or other data from which the TCD 100 is able to determine the particular preliminary detection. If the remote facility does not instruct the TCD 100 what adjustments are to be made, the TCD 100 may determine the adjustment(s) that is/are needed, and perform the adjustment(s), such as switching to a timed operation, so that the traffic flow in the direction corresponding to the malfunctioning sensor is periodically allowed for a predetermined time duration. The TCD 100 may store a table relating different events that cause the preliminary detections obtained in the step 205 to specific adjustments, and make the adjustments according to the table.

In step 290, an appropriate corrective action may be triggered or scheduled, such as signaling to schedule a visit by maintenance/repair personnel, signaling to schedule a towing operation, etc. This may be performed, for example, by the remote facility(ies); as another example, this step may be performed by the TCD 100 in response to receiving the notification in the step 285, perhaps by transmitting a request to the appropriate authority.

The process may then terminate at the flow point 299, to be repeated as needed or desired.

As a person skilled in the art would understand after careful perusal of this document including the attached drawings, certain analyses and decisions regarding the preliminary detection and/or the verifications can be done completely at the TCD 100, at a remote facility (or remote facilities, as the case may be), or with combined resources of both the TCD 100 and the remote facility(ies).

The processing/decisions made by the human analyzer(s) in the step 265 may be stored together with their corresponding still/video/lidar/radar/RF/other recordings and corresponding sensor data (such as the data from the state-affecting sensors), and subsequently used to train artificial intelligence (AI, which term includes statistical prediction, machine learning, neural networks, deep learning) to distinguish better between false and true GRs. In this way, the steps 220 and 250 may continue to be improved, to distinguish better between true and false GRs. Additionally, the information selected for transmission in the step 240 and corresponding receipt in the step 245 may also be refined through addition of information relevant to the making of “COSS REAL GR?” decisions and/or deletion or non-transmission of information that is not relevant to or useful for making of the decision.

FIG. 3 illustrates steps of a process 300 for verifying a preliminary detection of a UTGR, for example, when no change in state is received from a particular sensor for a long period of time. At flow point 301, the TCD 100 and other devices (if applicable) is (or are, as the case may be) powered-up, initialized, and ready to perform the steps of the process 300.

In step 305, a preliminary detection of a UTGR is obtained. The preliminary detection may be generated, for example, by the TCD 100, or received by the TCD 100 from another source such as a remote computer system. The preliminary detection may also originate from a person submitting a report to the remote computer system or directly to the TCD 100.

In step 310, the physical locations corresponding to the preliminary detection are identified. Physical locations that correspond to the preliminary detection are such locations from which a true GR associated with the UTGR may be generated. This step can be identical, similar, or analogous to the corresponding step 210 of the process 200.

Video recording(s) and/or still image(s) recordings of these locations during a long predetermined time period are then obtained (or have been previously obtained), in step 315, so that they can be examined. For example, the TCD 100 identifies such recordings based on the camera(s) 130 locations and directions in which they face (the cameras' orientations); as another example, the TCD 100 requests the recordings from one or more external cameras, basing the request on the relevant time (while no GRs were being received) and the identified physical locations from the step 310. The long predetermined time period may be based on the experience of the TCD 100. For example, if the TCD 100 experience is such that a particular sensor has always or almost always (at or above some relatively-high predetermined percentage of times, such as 90%) provided at least one GR within a period T, then the longest predetermined period may be set to T times a predetermined factor, for example, between 2 and 10.

In step 320, the video/still recordings are initially examined automatically, to determine whether an appropriate entity (e.g., a vehicle in case of an inductive loop sensor, a pedestrian in case of a pedestrian pushbutton) was present in the locations during the recorded period. A vehicle in the immediate proximity (sensing range) of the inductive loop sensor should have produced a GR, which GR was not detected/received. The automatic examination may include attempting to recognize a vehicle (even a small one, such as a bicycle) or another large object in the locations by the visual/IR/UV appearance/signature of the vehicle/object, by its radar/lidar appearance/signature, appearance/signature of another type of RF reflections, by its sound, and/or through other means. The step 320 may be identical, similar, or analogous to the step 220 of the process 200.

If the result of the automatic examination of the step 320 is conclusive or suggesting strongly that the UTGR is a real one, as determined in decision block 325, process flow continues to step 330. The result may be a COSS real UTGR if, for example, a vehicle or another large object is identified in the automatically-examined recordings, within maximum/typical sensing range of an inductive loop; and/or if a person waiting over some predetermined period such as one minute is identified in the automatically-examined recordings, within an arm's length (such as four feet) of a pushbutton. The step 330 transmits to the remote facility the video/still recordings together with a notification of the event (or events, when multiple vehicles/persons in the locations were identified in the recordings).

A result may be a COSS real UTGR result when the step 320 indicates with sufficient certainty (such as a probability greater than or not less than a predetermined threshold (e.g., between 50% and 100% or a probability greater than another predetermined threshold) that the UTGR was real, i.e., that a GR should have been sensed but was not. When the step 320 is designed to indicate either (1) a UTGR (a GR should have been sensed but was not sensed), or (2) not UTGR (no GR should have been received and was not received), the first indication (UTGR) is a COSS real UTGR result, the second indication is not. When the step 320 is designed to indicate one of three possibilities (1) UTGR, (2) uncertain, and (3) not UTGR (no GR), then only the first possibility (UTGR) is a COSS real UTGR result in some embodiments. When the result of the step 320 is designed to produce a range of possibilities between a certain UTGR and a certain not UTGR, then a COSS real UTGR result applies to all the possibilities indicating UTGR at or above a predetermined probability level, such as 50%-100% (or above another predetermined threshold) that a GR should have been sensed but was not sensed.

In step 332, which follows the step 330, the TCD 100 adjusts its operation (the operation of its state machine) to account for a bad sensor input; for example, the TCD 100 may switch to a timed operation, so that the traffic (whether vehicular or pedestrian) flow in the direction corresponding to the malfunctioning sensor is periodically allowed, despite not sensing a GR. Such operation may be programmed in the state machine even when the sensor is not malfunctioning; in this case, the time period may be shortened in response to the UTGR being real.

Process flow then advances to decision block 335, where the TCD 100 determines whether the malfunction has been cleared (while operating as adjusted in the step 332); clearance of the malfunction may be determined by receiving a notification from a remote facility to the effect that operation should return to normal, for example, because it was determined at the remote facility based on the information from the step 330 that there was no malfunction, or when the TCD 100 senses that the sensor input begins switching states at a later time. If the malfunction has been cleared, the TCD 100 clears the preliminary detection of the UTGR in step 340, and returns to normal operation. The process terminates at flow point 399, to be repeated as need or desired, for example, when triggered by another UTGR obtained/received in the step 305.

Returning to the decision block 325, if the result of the automatic examination of in the step 320 is negative, process flow continues to step 350, where the TCD 100 transmits to the remote facility(ies) the recordings and a notification that a UTGR was suspected but found not to exist. The remote facility may examine the recordings automatically and/or manually (engaging a human resource, which can be a crowdsourced resource) and come to the same or a different conclusion, may send a transmission to the TCD 100 that it should lengthen the predetermined period for recording in the process 300 or that the UTGR was in fact present, or simply monitor the notifications from the step 350 and take some action in response to an increased frequency (greater than a predetermined frequency) of such notifications. In embodiments, the process flow bypasses the step 350.

The process then terminates at the flow point 399, and can be repeated as needed or desired.

The TCD 100 may be configured to perform as a beacon, as is described below and elsewhere in this document. A beacon that is not a traffic control device may also be implemented as is described below and elsewhere in this document. A stand-alone beacon (or a beacon combined with some other functionality) may include components shown in FIG. 1, likely without the visual traffic control display(s) 135, the camera(s) 130, and/or the interface(s) 140.

For beacon operation, the TCD 100 is configured to transmit (e.g., broadcast, multicast, or simply transmit to a particular device) through a transmitter 120B a beacon signal that carries information sufficient for an appropriately-configured receiver (such as a receiver of a vehicle computer, a smart phone or another communication/computing mobile device, a dedicated navigation device, or a similar device, generally designated as a “receiving device”) to determine the distance from the receiving device to the TCD 100. This information, combined with the known geographic coordinates of the TCD 100, allows the vehicle receiver to determine its distance to the TCD 100 and its location, possibly with greater precision than would otherwise be possible. This is particularly useful in the presence of significant GPS multipath (“MP”), when GPS signals are blocked, when significant interference on the frequencies used by GPS is present, and when no GPS capability is available in the receiving device. But even when GPS works as designed, the distance measurement functionality may improve, perhaps substantially, on the location estimation capability of the receiving device. Note that the receiving device may employ the distance measurement (“DM”) techniques describe herein to measure distances to two or more beacons, and derive its location/position information from the multiple distance measurements, e.g., using trilateration and/or “other location information” as defined elsewhere in this document. Ambiguities may be resolved using various other information, such as map information.

The TCD 100 can emit an RF signal modulated with two, three, or more lower frequency signals, with known phase relationship(s) between or among the lower frequency signals (at the transmitter 120B, at a predetermined or otherwise known time); the lower frequency signals may, for example, be periodically phase locked (directly or indirectly) to the same source, or one of them may serve as a reference to the other(s), or some may be derived from another (or others) such as by frequency multiplication or division. The receiving device may receive the transmission from the TCD 100, downconvert the received signal (to baseband or IF) to extract the lower frequency signals, and determine the relative phase shift(s) between the lower frequency signals. Recall that the phase relationship at the TCD 100 is fixed at the predetermined time, and may be known to the receiving device (e.g., by convention and/or information received from the TCD 100, perhaps together with the RF signal modulated by the lower frequency signals, or computed based on two phase differences as will be shown, or received/derived from another source). From this information and the measurement of the phases of the lower frequency signals at the receiving device, the receiving device (such as a vehicle computer-receiver) can calculate the distance to the TCD 100. Because the TCD 100 is relatively close to the vehicle that is approaching it, the MP and other distorting effects between the vehicle and the TCD 100 may be manageable and the computed receiving device-to-TCD 100 distance is likely to be very close to the actual distance. The TCD 100 may encode the information regarding the predetermined time and the phase relationship at the TCD 100 and its own location coordinates onto the signal that the TCD 100 transmits. As has already been mentioned, the transmission may be omnidirectional, directional, or directional in the horizontal plane; and it may be a broadcast or a multicast or another type of transmission.

In embodiments, the beacon emits a modulated high frequency signal. The frequency of the emitted high frequency signal may be, for example, in the tens of megahertz (>10 MHz) range, in the hundreds of megahertz (>100 MHz) range, and in the GHz (>1 GHz) range; and the modulating beacon frequencies (as related to beacon operation discussed herein) and the differences between and among them may be, for example, at least two, three, four, five, six, or even more orders of magnitude lower; in embodiments, the modulation frequencies are under 100 KHz; in embodiments, the modulation frequencies are under 100 KHz, in embodiments, the modulation frequencies are under 10 KHz; in embodiments, the modulation frequencies are under 3 KHz; in embodiments, the differences between any two of the modulation frequencies are under 10 KHz, under 3 KHz, under 1 KHz. This type of frequency relationships helps ensure that the multiple frequencies in the modulation band are generally subjected to similar MP, Doppler shift, and other distorting effects, and also helps in resolving distance ambiguity due to phase rotation, as will be seen. The in-band low frequency modulation signals may be generated so that their phase difference at the time of arrival at the receiving device (such as an automobile with a vehicle computer) allows the receiver to compute the distance to the beacon to within a small uncertainty distance interval, for example, less than 15 meters (50 feet), less than five meters (16 feet), less than 1 meter (3.3 feet), less than 25 centimeters (10 inches), and in some examples even less. In embodiments, the ambiguity in the distance due to repeating wavelengths of the low frequency signals is much greater than what cannot be resolved based on “other location information” available to the receiver, as is discussed below; the ambiguity may be, for example, over one kilometer, over ten kilometers and greater, allowing for the ambiguity to be resolved using other location information or even avoiding the ambiguity altogether. Moreover, in embodiments, the receiving device need not have knowledge of the time the lower frequency signals were synchronized (their phase relationships were fixed), but can derive this information (time) from multiple relative phase shifts of the received lower frequency signals (such as three or more lower frequency signals) at the receiving device, and a known “synchronization scheme.”

Beginning with the basic phase equation of a propagating sinusoidal wave of frequency f (angular frequency ω=2*π*f) and wavelength λ=c/f (c being the speed of propagation, i.e., speed of light in the air):

${\left. {P = {2*\pi*\left( {{f*t} - \frac{x}{\lambda}} \right)}} \right) + \phi},$ where P is phase, t is time, x is distance, and φ is the phase at t=0 and x=0. This is equation (1).

Consider two modulation frequencies/wavelengths f₁/λ₁ and f₂/λ₂ on a carrier F₀/λ₀, and emission from the beacon such that f₁ and f₂ are at the same given phase at the time/location of emission (i.e., φ in equation (1)), which can be assumed to be zero without loss of generality. The signals on the two frequencies may be synchronized in various ways, for example, by simultaneously resetting feedback frequency dividers in phase locked loops or in synthesizers that generate the two frequencies. The corresponding wavelengths λ₁ and λ₂ are long relative to λ₀, and each wavelength corresponds to 360° or 2*π radians at its corresponding frequency. Thus, one degree of phase shift due to travel is equivalent to a distance of λ₁/360 at f₁, and to a distance of λ₂/360 at f₂; one radian of phase shift is equivalent to a distance of λ₁/(2π) at f₁, and to a distance of λ₂/(2π) at f₂.

Defining P1 and P2 as the phases of f₁ and f₂, respectively, and substituting the variables into the phase equation (1) results in:

$\begin{matrix} {{P\; 1} = {{\left( {2*\pi*\left( {{f_{1}*t} - \frac{D}{\lambda_{1}}} \right)} \right)\mspace{14mu}{and}\mspace{11mu} P\; 2} = {\left( {2*\pi*\left( {{f_{2}*t} - \frac{D}{\lambda_{2}}} \right)} \right).}}} & (2) \end{matrix}$

Define Δ_(phA)=P1−P2; Δ_(fA)=(f₁−f₂); and Δ_(λA)=(λ₂−λ₁). The phase difference is given by:

$\begin{matrix} {\Delta_{phA} = {{\left( {2*\pi*\left( {{f_{1}*t} - \frac{D}{\lambda_{1}}} \right)} \right) - \left( {2*\pi*\left( {{f_{2}*t} - \frac{D}{\lambda_{2}}} \right)} \right)} = \left( {{2*\pi*\left( {{\left( {f_{1} - f_{2}} \right)*t} - \frac{D}{\lambda_{1}} + \frac{D}{\lambda_{2}}} \right)} = {{2*\pi*\left( {{\Delta_{fA}*t} - \left( {\frac{D}{\lambda_{1}} - \frac{D}{\lambda_{2}}} \right)} \right)} = {2*\pi*\left( {{{\Delta_{fA}*t} - \left( \frac{D*\left( {\lambda_{2} - \lambda_{1}} \right)}{\lambda_{1}*\lambda_{2}} \right)} = {2*\pi*{\left( {{\Delta_{fA}*t} - \left( \frac{D*D_{\lambda\; A}}{\lambda_{1}*\lambda_{2}} \right)} \right).}}} \right.}}} \right.}} & (3) \end{matrix}$

Rearranging terms:

$\begin{matrix} {{\Delta_{phA} = {{t*\left( {2*\pi*\Delta_{fA}} \right)} - {D*\left( \frac{2*\pi*\Delta_{\lambda\; A}}{\lambda_{1}*\lambda_{2}} \right)}}},{and}} & (4) \\ {{D*\left( \frac{2*\pi*\Delta_{\lambda\; A}}{\lambda_{1}*\lambda_{2}} \right)} = {{t*\left( {2*\pi*\Delta_{fA}} \right)} - {\Delta_{phA}.}}} & (5) \end{matrix}$

The distance D can now be isolated:

$\begin{matrix} {D = {\frac{\left( {{t*\left( {2*\pi*\Delta_{fA}} \right)} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}.}} & (6) \end{matrix}$

To estimate the distance D, the receiving device (at the vehicle, smart phone, etc.) needs to know t, which is the time elapsed from the moment f₁ and f₂ were synchronized at the beacon; this invokes two related problems. First, the receiving device needs to know when the beacon synchronizes f₁ and f₂ according to the beacon's time base (clock); second, because the receiving device and the beacon use different physical clocks, the times at the beacon and at the receiving device may differ; the beacon's time reference may not be known precisely by the receiving device. Still another problem is that Δ_(ph)'s (Δ_(phA) and generally all phases and phase differences) are subject to ambiguity due to the rotating nature of phases: a phase difference of α degrees may appear the same as (α+n*360) degrees n being an integer; for example, 30 degrees may appear the same as 390 degrees, 750 degrees, etc.

These problems may become easier if the frequencies f₁ and f₂ are chosen so that they are low and close to each other. To give a concrete example, assume that f₁=1 KHz and f₂=1.1 KHz, with the corresponding wavelengths of these modulation frequencies being λ₁=300,000 meters and λ₂=272,727.27 . . . meters. Then, Δ_(phA) (in degrees)=0.00012*D−36,000*t. This examples demonstrates that at a given distance D₁ the phase difference Δ_(ph) rotates at 100 Hz, and at a given time t₁ the phase difference repeats every 3,000,000 meters. More generally, the phase differential Δ_(ph) rotates (at a set distance from the beacon) at the frequency Δ_(fA), the difference between the two frequencies f₁ and f₂; and the phase differential Δ_(ph) repeats (at a set time) at the distance of

$\frac{c}{\Delta_{f}},$ c being the speed of light. Thus, Δ_(f) can be thought of as the “frequency” of the phase difference at a given distance; and

$\frac{c}{\Delta_{f}}$ can be thought of as the “wavelength” of the phase difference.

The concrete example of the preceding paragraph illustrates that the ambiguity due to the rotation of the phases may be resolved by choosing the f₁ and f₂ frequencies properly; 300,000 meters (which is ten times less than the ambiguity distance computed above) or about 180 miles is a sufficiently long distance to be resolved by a great many types of “other location information”; indeed, given the range of transmissions from TCD beacons and other beacons, there may be no real ambiguity in the first place. Thus, in embodiments, the “frequency” of the phase difference is selected so that the “wavelength” of the phase difference is much greater (>×10) than the maximum design range of the beacon transmissions; in embodiments, the “frequency” of the phase difference is selected so that the “wavelength” of the phase difference is greater than 1 kilometer; greater than 10 kilometers; greater than 25 kilometers; greater than 100 kilometers, as is the case in the concrete example above; and greater than 1000 kilometers. When more than two frequencies are involved, such as in the cases of three frequencies (f₁, f₂, f₃) and four frequencies (f₁, f₂, f₃, f₄) discussed below, the same limitations on the frequencies may be applied to all of them and to each of the frequency differences between each pair of such frequencies.

Turning next to the three-frequency case, introduce a new modulation frequency f₃ (such that, for convenience of discussion, λ₁<λ₂, λ₁<λ₃, and therefore f₁>f₂, f₁>f₃, and f₂≠f₃). At time t and distance D, the phase of f₃ is:

$\begin{matrix} {{P\; 3} = {\left( {2*\pi*\left( {{f_{3}*t} - \frac{D}{\lambda_{3}}} \right)} \right).}} & (7) \end{matrix}$

Here are the additional definitions for this three-frequency case: Δ_(phB)=P1−P3; Δ_(fB)=(f₁−f₃); Δ_(λB)=(λ₃−λ₁). With these definitions, the following should hold, with the distance D being the same whether measured based on the phase difference Δ_(phB) or the phase difference Δ_(phA)

$\begin{matrix} {D = {\frac{\left( {{t*\left( {2*\pi*\Delta_{fB}} \right)} - \Delta_{phB}} \right)*\lambda_{1}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}} = {\frac{\left( {{t*\left( {2*\pi*\Delta_{fA}} \right)} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}.}}} & (8) \end{matrix}$

Re-writing, rearranging, and isolating t obtains:

$\begin{matrix} {{{\frac{t*2*\pi*\Delta_{fB}*\lambda_{1}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}} - \frac{\Delta - {{phB}*\lambda_{1}*\lambda_{3}}}{2*\pi*\Delta_{\lambda\; B}}} = {\frac{t*2*\pi*\Delta_{fA}*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}} - \frac{\Delta_{phA}*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}}};} & (9) \\ {{{t*\left( {\frac{\Delta_{fB}*\lambda_{1}*\lambda_{3}}{\Delta_{\lambda\; B}} - \frac{\Delta_{fA}*\lambda_{1}*\lambda_{2}}{\Delta_{\lambda\; A}}} \right)} = {\frac{\Delta_{phB}*\lambda_{1}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}} - \frac{\Delta_{phA}*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}}};} & (10) \\ {{{t*\left( \frac{{\Delta_{fB}*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{1}*\lambda_{2\;*\Delta_{\lambda\; B}}}}{\Delta_{\lambda\; B}*\Delta_{\lambda\; A}} \right)} = \frac{\left( {{\Delta_{phB}*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{{phA}\;}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)}{2*\pi*\Delta_{\lambda\; B}*\Delta_{\lambda\; A}}};{and}} & (11) \\ {t = {\frac{\left( {{\Delta_{phB}*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{{ph}\; A}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)*\Delta_{\lambda\; B}*\Delta_{\lambda\; A}}{2*\pi*\Delta_{\lambda\; B}*\Delta_{\lambda\; A}*\left( {{\Delta_{fB}*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)} = {\frac{\left( {{\Delta_{phB}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{phA}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)}{2*\pi*\left( {{\Delta_{fB}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)}.}}} & (12) \end{matrix}$

Note that in the last equation, the frequencies f's, the associated wavelengths λ's, and their differences and Δ_(fA)/Δ_(fB) and Δ_(λA)/Δ_(λB) should be known to the receiving device, and the phase differences Δ_(phA) and Δ_(phB) (the f₁-to-f₂ and f₁-to-f₃ phase differences) are measurable by the receiving device. The receiving device can therefore compute t, e.g., from equation (12), and then D from, e.g., equation (8).

To avoid ambiguity due to the repeating nature of phase change, the maximum operational distances and the frequencies (f₁, f₂, f₃) may be selected appropriately. Thus, as with the concrete example above, the frequency difference Δ_(fB) may be made small, such as of the order of or equal to Δ_(fA). Recall that Δ_(fA) was 100 Hz in the concrete example, and the phase differential repeated at the distance of

$\frac{c}{\Delta_{f}}.$ To extend the concrete example, f₃ may be set to 1.2 KHz, and Δ_(fB) should then repeat (at a set time) every 1,500,000 meters; recall that Δ_(fA) repeats every 3,000,000 meters. Thus ambiguity should not be a problem with appropriately-selected frequencies and frequency spacings.

The use of three modulation frequencies (f₁, f₂, f₃) can be extended to, for example, four modulation frequencies (f₁, f₂, f₃, f₄) with their corresponding wavelengths (λ₁, λ₂, λ₃, λ₄). For convenience, let λ₄<λ₃ and therefore f₄>f₃. If the phase of the frequency f₄, P4, is also synchronized simultaneously with the phases of f₁, f₂, f₃ at the beacon, and the phases are measured at the same receiving device at the same time, then

${{P\; 3} = \left( {2*\pi*\left( {{f_{3}*t} - \frac{D}{\lambda_{3}}} \right)} \right)};{{{and}\mspace{14mu} P\; 4} = {\left( {2*\pi*\left( {{f_{4}*t} - \frac{D}{\lambda_{4}}} \right)} \right).}}$ These are equations (13).

Similar to the symbolism used above, define Δ_(phA)=P4−P3; Δ_(fB)=(f₄−f₃); and Δ_(λB)=(λ₃−λ₄). Rewriting equations (13) above to express the phase difference between P4 and P3:

$\begin{matrix} {{{P\; 4} - {P\; 3}} = {\Delta_{phB} = {{\left( {2*\pi*\left( {{f_{4}*t} - \frac{D}{\lambda_{4}}} \right)} \right) - \left( {2*\pi*\left( {{f_{3}*t} - \frac{D}{\lambda_{3}}} \right)} \right)} = {{t*2*\pi*\left( {f_{4} - f_{3}} \right)} - {D*2*\pi*{\left( {\frac{1}{\lambda_{4}} - \frac{1}{\lambda_{3}}} \right).}}}}}} & (14) \end{matrix}$

Re-writing, rearranging, and isolating t obtains:

$\begin{matrix} \begin{matrix} {\mspace{20mu}{\Delta_{phB} = {{t*2*\pi*\Delta_{fB}} - {D*2*\pi*\frac{\lambda_{3} - \lambda_{4}}{\lambda_{4}*\lambda_{3}}}}}} \\ {{= {{t*\left( {2*\pi*\Delta_{fB}} \right)} - {D*\left( {2*\pi*\frac{\Delta_{\lambda\; B}}{\lambda_{4}*\lambda_{3}}} \right)}}};} \end{matrix} & (15) \\ {\mspace{20mu}{{{D*\left( {2*\pi*\frac{\Delta_{\lambda\; B}}{\lambda_{4}*\lambda_{3}}} \right)} = {{t*\left( {2*\pi*\Delta_{fB}} \right)} - \Delta_{phB}}};}} & (16) \\ {{D = {\frac{\left( {{t*\left( {2*\pi*\Delta_{fB}} \right)} - \Delta_{phB}} \right)*\lambda_{4}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}} = \frac{\left( {{t*\left( {2*\pi*\Delta_{fA}} \right)} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}}};} & (17) \\ {{\frac{\left( {{t*\left( {2*\pi*\Delta_{fB}} \right)} - \Delta_{phB}} \right)*\lambda_{4}*\lambda_{3}}{\Delta_{\lambda\; B}} = \frac{\left( {{t*\left( {2*\pi*\Delta_{f\; A}} \right)} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}}{\Delta_{\lambda\; A}}};} & (18) \\ {{{\left( {{t*\left( {2*\pi*\Delta_{fB}} \right)} - \Delta_{phB}} \right)*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} = {\left( {{t*\left( {2*\pi*\Delta_{fA}} \right)} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}};} & (19) \\ {{{t*2*\pi*\left( {{\Delta_{fB}*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)} = {{\Delta_{phB}*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{phA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}}};{and}} & (20) \\ {\mspace{20mu}{t = {\frac{\left( {{\Delta_{phB}*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{phA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)}{2*\pi*\left( {{\Delta_{fB}*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)}.}}} & (21) \end{matrix}$

In the last equation, Δ_(phA) and Δ_(phB), the f₁-to-f₂ and f₄-to-f₃ phase differences, are measurable at the receiving device, and the other parameters (the wavelengths, frequencies, and their differences) are known. Therefore, t, the time elapsed from synchronization of the phases of the frequencies can be computed, e.g., from equation (21). The distance D can then be computed, e.g., from equation (17).

Recall that in the above it was assumed that the phases of the frequencies (f₁, f₂, f₃) and (f₁, f₂, f₃, f₄) were synchronized by setting them to the same value at t=0, at the beacon. It was assumed that the phase value was zero, but as a person skilled in the art would understand after careful perusal of this document and the attached drawings, all that is needed is for the receiving device to know the scheme for setting the phases to known values at beacon times that the receiving device knows or can obtain. Based on this knowledge (of times and corresponding phases at the beacon), the knowledge of the frequencies wavelengths, and the measured phase differences, the receiving device can compute the distance D for arbitrary (but known) initial phases. Extending the three-frequency case above (f₁, f₂, and f₃) so that each frequency signal has its own phase φ, the equations for the phases become:

$\begin{matrix} {{{P\; 1} = \left( {{2*\pi*\left( {{f_{1}*t} - \frac{D}{\lambda_{1}}} \right)} + \phi_{1}} \right)};} & (22) \\ {{{P\; 2} = \left( {{2*\pi*\left( {{f_{2}*t} - \frac{D}{\lambda_{2}}} \right)} + \phi_{2}} \right)};{and}} & (23) \\ {{P\; 3} = {\left( {{2*\pi*\left( {{f_{3}*t} - \frac{D}{\lambda_{3}}} \right)} + \phi_{3}} \right).}} & (24) \end{matrix}$

Let f₁>f₂ and λ₂>λ₁, λ₁<λ₃ and therefore f₁>f₃ and f₂≠f₃; and as before, define Δ_(phA)=P1−P2; Δ_(fA)=(f₁−f₂); Δ_(λA)=(λ₂−λ₁); Δ_(phB)=P1−P3; Δ_(fB)=(f₁−f₃); Δ_(λB)=(λ₃−λ₁). Also define: Δ_(ϕA)=(ϕ₁−ϕ₂); and Δ_(ϕB)=(ϕ₁−ϕ₃). These equations now follow:

$\begin{matrix} {{\Delta_{phA} = {{{P\; 1} - {P\; 2}} = {\left( {2*\pi*\left( {{f_{1}*t} - \frac{D}{\lambda_{1}}} \right)} \right) - \left( {2*\pi*\left( {{f_{2}*t} - \frac{D}{\lambda_{2}}} \right)} \right) + \left( {\phi_{1} - \phi_{2}} \right)}}};} & (25) \\ {\mspace{20mu}{{\Delta_{phA} = {\left( {2*\pi*\left( {{\left( {f_{1} - f_{2}} \right)*t} - \frac{D}{\lambda_{1}} + \frac{D}{\lambda_{2}}} \right)} \right) + \left( {\phi_{1} - \phi_{2}} \right)}};}} & (26) \\ {\mspace{20mu}{\Delta_{phA} = \left( {{{2*\pi*\left( {{\Delta_{fA}*t} - \frac{D}{\lambda_{1}} + \frac{D}{\lambda_{2}}} \right)} + \Delta_{\phi\; A}};} \right.}} & (27) \\ {{\Delta_{phA} = {{{t*\left( {2*\pi*\Delta_{fA}} \right)} - {D*2*\pi*\frac{\lambda_{2} - \lambda_{1}}{\lambda_{1}*\lambda_{2}}} + \Delta_{\phi\; A}} = {{t*\left( {2*\pi*\Delta_{fA}} \right)} - {D*2*\pi*\left( \frac{\Delta_{\lambda\; A}}{\lambda_{1}*\lambda_{2}} \right)} + \Delta_{\phi\; A}}}};} & (28) \\ {\mspace{20mu}{{{D*2*\pi*\left( \frac{\Delta_{\lambda\; A}}{\lambda_{1}*\lambda_{2}} \right)} = {{t*\left( {2*\pi*\Delta_{fA}} \right)} + \Delta_{\phi\; A} - \Delta_{phA}}};}} & (29) \\ {{D = {{{t*\left( \frac{2*\pi*\Delta_{fA}*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}} \right)} + \frac{\left( {\Delta_{\phi\; A} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}} = \frac{\left( {{t*\left( {2*\pi*\Delta_{fA}} \right)} - \left( {\Delta_{phA} - \Delta_{\phi\; A}} \right)} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}}};} & (30) \\ {{D = {\frac{\left( {{t*\left( {2*\pi*\Delta_{fB}} \right)} - \left( {\Delta_{phB} - \Delta_{\phi\; B}} \right)} \right)*\lambda_{1}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}} = \frac{\left( {{t*\left( {2*\pi*\Delta_{fA}} \right)} - \left( {\Delta_{phA} - \Delta_{\phi\; A}} \right)} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}}};} & (31) \\ {{{{t*2*\pi*\Delta_{fB}*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\left( {\Delta_{phB} - \Delta_{\phi\; B}} \right)*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}}} = {{t*2*\pi*\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}} - {\left( {\Delta_{phA} - \Delta_{\phi\; A}} \right)*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}}};} & (32) \\ {{{t*2*\pi*\left( {{\Delta_{fB}*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)} = {{\left( {\Delta_{phB} - \Delta_{\phi\; B}} \right)*\lambda_{1}*\lambda_{3}*\Delta_{\lambda\; A}} - {\left( {\Delta_{phA} - \Delta_{\phi\; A}} \right)*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}}};{and}} & (33) \\ {\mspace{20mu}{t = {\frac{{\left( {\Delta_{phB} - \Delta_{\phi\; B}} \right)*\lambda_{3}*\Delta_{\lambda\; A}} - {\left( {\Delta_{phA} - \Delta_{\phi\; A}} \right)*\lambda_{2}*\Delta_{\lambda\; B}}}{2*\pi*\left( {{\Delta_{fB}*\lambda_{3}*\Delta_{\lambda\; A}} - {\Delta_{fA}*\lambda_{2}*\Delta_{\lambda\; B}}} \right.}.}}} & (34) \end{matrix}$

Given the knowledge of the frequencies/wavelengths and the initial phases (ϕ₁, ϕ₂, ϕ₃) and therefore their differences (Δ_(ϕA), Δ_(ϕB)), and given the measured phase differences at the receiving device (Δ_(phA), Δ_(phB)), the receiving device can calculate the time t from, e.g., equation (34), and then the distance D from, e.g., equation (30).

Extending the four-frequency case above (f₁, f₂, f₃, and f₄) so that each frequency signal has its own initial phase ϕ (at t=0, x=0), the equations for the phases are:

$\begin{matrix} {{{P\; 1} = \left( {{2*\pi*\left( {{f_{1}*t} - \frac{D}{\lambda_{1}}} \right)} + \phi_{1}} \right)};} & (35) \\ {{{P\; 2} = \left( {{2*\pi*\left( {{f_{2}*t} - \frac{D}{\lambda_{2}}} \right)} + \phi_{2}} \right)};} & (36) \\ {{{P\; 3} = \left( {{2*\pi*\left( {{f_{3}*t} - \frac{D}{\lambda_{3}}} \right)} + \phi_{3}} \right)};{and}} & (37) \\ {{P\; 4} = {\left( {{2*\pi*\left( {{f_{4}*t} - \frac{D}{\lambda_{4}}} \right)} + \phi_{4}} \right).}} & (38) \end{matrix}$

For convenience, let f₁>f₂, f₄>f₃, λ₂>λ₁, λ₁<λ₃; and define Δ_(phA)=P1−P2, Δ_(fA)=(f₁−f₂), Δ_(λA)=(λ₂−λ₁), Δ_(phB)=P4−P3, Δ_(fB)=(f₄−f₃); Δ_(λB)=(λ₃−λ₄), Δ_(ϕA)=(ϕ₁−ϕ₂), Δ_(ϕB)=(ϕ₄−ϕ₃). These equations now follow:

$\begin{matrix} {{\Delta_{phA} = {{{P\; 1} - {P\; 2}} = {{t*\left( {2*\pi} \right)*\left( {f_{1} - f_{2}} \right)} - \left( {D*\left( {\frac{2*\pi}{\lambda_{1}} - \frac{2*\pi}{\lambda_{2}}} \right)} \right) + \phi_{1} - \phi_{2}}}};} & (39) \\ {\mspace{20mu}{{\Delta_{phA} = {{t*2*\pi*\Delta_{fA}} - {D*2*\pi*\left( \frac{\lambda_{2} - \lambda_{1}}{\lambda_{1}*\lambda_{2}} \right)} + \Delta_{\phi\; A}}};}} & (40) \\ {\mspace{20mu}{{\Delta_{phA} = {{t*2*\pi*\Delta_{fA}} - {D*2*\pi*\left( \frac{\Delta_{\lambda\; A}}{\lambda_{1}*\lambda_{2}} \right)} + \Delta_{\phi\; A}}};}} & (41) \\ {\mspace{20mu}{{\Delta_{phB} = {{t*2*\pi*\Delta_{fB}} - {D*2*\pi*\left( \frac{\Delta_{\lambda\; B}}{\lambda_{4}*\lambda_{3}} \right)} + \Delta_{\phi\; B}}};}} & (42) \\ {{D = {{{t*\frac{2*\pi*\Delta_{fA}*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}} + \frac{\left( {\Delta_{\phi\; A} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}}{2*\pi*\Delta_{\lambda\; A}}} = {{t*\frac{2*\pi*\Delta_{{fB}\;}*\lambda_{4}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}}} + \frac{\left( {\Delta_{\phi\; B} - \Delta_{phB}} \right)*\lambda_{4}*\lambda_{3}}{2*\pi*\Delta_{\lambda\; B}}}}};} & (43) \\ {{{t*\frac{2*\pi*\left( {{\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}} - {\Delta_{fB}*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}}} \right)}{2*\pi*\Delta_{\lambda\; A}*\Delta_{\lambda\; B}}} = \frac{{\left( {\Delta_{\phi\; B} - \Delta_{phB}} \right)*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} - {\left( {\Delta_{\phi\; A} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}}{2*\pi*\Delta_{\lambda\; A}*\Delta_{\lambda\; B}}};} & (44) \\ {and} & \; \\ {t = {\frac{\left( {{\left( {\Delta_{\phi\; B} - \Delta_{phB}} \right)*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}} - {\left( {\Delta_{\phi\; A} - \Delta_{phA}} \right)*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}}} \right)}{2*\pi*\left( {{\Delta_{fA}*\lambda_{1}*\lambda_{2}*\Delta_{\lambda\; B}} - {\Delta_{fB}*\lambda_{4}*\lambda_{3}*\Delta_{\lambda\; A}}} \right)}.}} & (45) \end{matrix}$

The time t can be computed, e.g., from the last equation, given the receiving device's knowledge of (i) the predetermined frequencies (f₁, f₂, f₃, and f₄), their corresponding wavelengths (λ₁, λ₂, λ₃, and λ₄), the frequency and wavelength differences Δ_(fA)/Δ_(fB) and Δ_(λA)/Δ_(λB); (ii) the measured phase differences Δ_(phA) and Δ_(phB); and (iii) the knowledge of the initial phases (ϕ₁, ϕ₂, ϕ₃, ϕ₄, and/or information from which the initial phases can be determined at the receiving device) and their differences Δ_(ϕA)/Δ_(ϕB). The distance, D, can then be computed at the receiving device, e.g., from equation (43). The initial phases (ϕ₁, ϕ₂, ϕ₃, ϕ₄ in case of a four-frequency implementation or ϕ₁, ϕ₂, ϕ₃ in case of a three-frequency implementation) may be set (be predetermined) by convention so that the receiving device (and possibly other receiving devices) knows them a priori; they may also be transmitted (broadcast, multicast, otherwise transmitted), for example, by the TCD/beacon and/or other systems/devices. In embodiments, the TCD/beacon transmits the initial phases (synchronization scheme) in the signal on F₀, possibly together with other information; thus, the modulation signals using the frequencies used for DM (f₁, f₂, f₂, or f₁, f₂, f₃, f₄) may be transmitted together with the additional information, including the initial phases. Similarly, when the initial phases of the signals are the same (e.g., zero degrees or the same non-zero value), this information may also be transmitted by the TCD/beacon or otherwise, or pre-set by convention. Additionally, the coordinates of the TCD/beacon may be transmitted in the same manner or otherwise. The zero phase value for the multiple modulation frequencies (at t=0, D=0) and the simultaneous synchronization of the modulation frequencies, however, are convenient for computational purposes and also for ease of hardware implementation. It may also be convenient to use three frequencies rather than four or more, though addition of a fourth frequency provides redundancy and allows a consistency check to be performed by computing the distance from different frequency deltas.

FIG. 4A illustrates steps of a process 400 for transmitting signals that facilitate distance measurement. The process 400 may be performed, for example, at a beacon such as the TCD 100 or a non-TCD beacon.

At flow point 401, the beacon is powered-up, initialized, synchronized (e.g., to a GPS clock), and ready to perform the steps of the process.

In step 405, the beacon generates a carrier (F₀) and multiple low and closely-spaced modulation frequencies used for distance measurement (f₁, f₂, f₃, . . . ).

In step 410, the beacon synchronizes the phases of the multiple low modulation frequencies. The multiple modulation frequencies may be synchronized at a predetermined time, for example, according to a schedule known to multiple receivers (vehicle computers, smart phones, navigation devices, etc.); this may be done periodically to avoid ambiguity in phase due to passage of time and the consequent phase rotation, as was seen in the derivation of the equations above, the receiving device might operate without precise knowledge of the time of synchronization of the phases, as long as the ambiguity is avoided. The phases may be set to the same value, e.g., zero degrees/radians, or to another value known or obtainable by the receiving device(s), or the respective phases of the different signals may be set to different values (for the different modulation frequencies f) known to or obtainable by the receiving device(s). Thus, as used in this context, “synchronizing” means setting the phases at the beacon to known/predetermined values; “synchronizing” to the same phase value means that the phases of the three or more frequencies f's are each set to the same value, which may but need not be zero degrees/radians; more generally, “synchronizing” may set each of the frequencies f to a known/predetermined phase value, and the phase values need not be the same. The receiving device should know the phase relationships between frequency pairs at the beacon, and the times when synchronizations take place so that the receiving device can compute the distance D) from the three or four phases (P1, P2, P3; or P1, P2, P3, P4) measured by the receiving device, as was shown above; in this document, data sufficient for this purpose is referred to as the “synchronization scheme” of the DM transmission.

In step 415, the beacon generates and emits a carrier signal modulated with the multiple synchronized frequencies. The signal may be of relatively short duration, such as a few milliseconds (e.g., 1-100 milliseconds); the duration may also be longer, and shorter durations are not necessarily excluded; in embodiments, however, the duration is at least as long as a large portion (e.g., >20%) of the period of the lowest of the modulation frequencies f_(n) used for distance measurement, and in embodiments, the duration is longer than the period, for example, at least several (say 3-20) periods of the lowest of the modulation frequencies f_(n); other durations are not necessarily excluded. The emitted signal may include additional data, for example: a unique identifier of the beacon, geographic coordinates of the beacon, the “synchronization scheme,” the “TCD state” and “time to”/“likelihood of” change in the state data described below, and still other data. The additional data may also or instead be transmitted separately, using another signal emitted by the beacon.

In decision block 420, the beacon determines whether time has come to repeat the steps 410/415. If the time to repeat has come, process flow returns to the step 410, for re-synchronization. Otherwise, the process flow continues to loop in the decision block 420. Thus, this decision block may be essentially a wait loop, though the beacon and other apparatus may be performing other steps at the same time, which is generally the case with all steps/decision described in this document. The synchronization of the step 410 and the generation/emission of the step 415 may be performed periodically, for example, between every 100 milliseconds to every few (e.g., one-to-ten) seconds. Other periods are not necessarily excluded. Generally, the process may be repeated so that the receiving device(s) using the beacon's signal for distance measurement may update their distance measurements in real time, such as before their location changes by more than a few meters at fastest moving speeds expected in the beacon's vicinity (reach of the beacon's transmission of the step 415).

In variants, the step 415 is repeated more often than the step 410, i.e., two or more emissions in the step 415 are performed following the synchronization of the step 410. FIG. 4B illustrates steps of a process 450 implementing this technique.

FIG. 5 illustrates steps of a process 500 for estimating distance between a receiving device and a beacon. The process 500 may be performed, for example, by a vehicle computer, smart phone, computer, tablet, a dedicated navigation device, or another device. Generally, the receiving device is a mobile (here meaning movable in ordinary usage) device, while the beacon is stationary, though generally each of the beacon and the receiving device may be stationary or mobile, and may change their mobility status (mobile-to-stationary and vice versa) at times.

At flow point 501, the receiving device is powered up, initialized, synchronized (for example, to a GPS clock), and ready to perform the steps of the process.

In step 505, the receiving device receives a signal from the beacon. For example, the receiving device receives the signal transmitted by the beacon in the step 415 of the processes 400/450.

In step 510, the receiving device extracts from the received beacon signal the modulation frequencies (e.g., f₁, f₂, f₃, and possibly more). This step may include downconverting the received beacon signal to baseband or intermediate frequency, and extracting/decoding the other information in the beacon's signal (such as coordinates of the beacon and the synchronization scheme/parameters).

In step 515, the receiving device determines at least two phase differences between/among the modulation frequencies, such as Δ_(phA) and λ_(phB), as has been explained above in relation to the three-frequency cases and the four-frequency cases For example, the modulation frequencies can be sampled by a high frequency clock and differences between times of transition can be determined; as another example, pairs of the modulation frequencies can be mixed together and the resulting low-frequency signal examined.

In step 520, the receiving device computes the distance to the beacon (or estimates the distance). The numbered equations (1)-(45) above relating the distance D, time from synchronization of phases at the beacon t, the modulation frequencies/wavelengths fs and λs, the phase differences at arrival at the receiving device Δ_(phA)/Δ_(hB), and the initial phases φ's can be used for this purpose; see particularly the three-frequency examples and the four-frequency examples. If there is ambiguity (due to the phase rotation), the distance estimate may be combined with “other location information,” as this expression is explained below.

In step 525, the receiving device uses the distance estimate calculated in the step 520, possibly in combination with other information, for example, to affect power train operation, braking, and other functions. In examples, a vehicle computer changes deceleration/acceleration rates based on the measure distance/position, changes a decision regarding gear selection or transmission ratio selection, changes a decision regarding starting/stopping an engine, changes a decision regarding regenerative-versus-conventional braking, or changes/makes another type of decision.

The process 500 may terminate at flow point 599, to be repeated as needed or desired.

As can be seen from the above discussion, when the phases of frequencies (f₁, f₂, f₃, or more) are simultaneously synchronized at the beacon and then measured at the receiver, the receiver can calculate its distance from the beacon based on the measured phase differences and the knowledge of the synchronization scheme. The distance may be calculated with substantial accuracy even in the absence of the receiver having a precise knowledge of the clock reference of the beacon. The clocks at the receiver and the beacon may in fact be synchronized using GPS, and the distance from the beacon can be calculated based on just two frequencies, e.g., f₁ and f₂, subject to the time uncertainty resulting from the use of the GPS clock. When using phase difference between two frequencies, the distance inaccuracy may be c (the speed of light) multiplied by the GPS time uncertainty. If the time uncertainty is 40 ns, for example, the distance uncertainty is about 12 meters. In the cases of physical proximity of the beacon and the receiver (e.g., <10 kilometers), the time uncertainty between their respective clocks may be substantially less than the GPS clock jitter; beacon-receiver distance determination may then rely on two-frequency phase difference, for example, based on the two-equation case, equations (1)-(6) above. Multipath, however, may have substantial effect, particularly on the roads with other vehicles (large reflectors) in the immediate vicinity of the receiver and/or the beacon.

To mitigate MP effects, the beacon may be mounted relatively high above the roadway, for example, at the same height and/or in the same enclosure as the VTCD(s) 135. In embodiments, the beacon's antenna(s) transmitting the DM frequencies is at least ten meters above ground level; in other embodiments, however, the beacon may be flush or even slightly underneath the roadway surface, preferably with a clear RF path to the surface. But heights between ground level and ten-meter elevation are not necessarily excluded.

Another way to deal with MP effects is to employ multiple “fingers” at the receiver, each finger configured to receive a single MP component. Such use of receiver “fingers” is known in the design of rake receivers. Here, however, the signals received at each of the fingers are inspected to identify the earliest MP component; the earliest component should correspond to line-of-sight (“LoS”) reception of the beacon's transmission (assuming the beacon is LoS to the receiving device). The LoS component can then be processed as has been described, to determine the distance to the beacon.

In embodiments, the receiving device includes a rake receiver, which it uses to identify the transmission from the beacon with MP gain. Once the receiving device has identified the beacon transmission, it uses the knowledge of the transmission to extract the earliest MP component. In embodiments, the receiving device uses the earliest MP component from the corresponding finger of the rake receiver.

The receiving device may combine the distance to the TCD 100 information with road map information and other location information to obtain a highly accurate estimate of the global position and position relative to the TCD 100. The “other location information” of the preceding sentence (and as used in other places of this document) may include (GPS-provided location information, which may be useful even when not quite accurate because of receiver limitations, MP, and/or other factors; dead-reckoning information; map information; and distance from one or more other beacons, including TCDs with the beacon functionality described above.

There are other techniques for measuring the vehicle-TCD 100 distance, including transponder-based techniques. See, generally, David Munoz el al, Position Location Techniques and Applications (1st Edition, ISBN-13: 978-1402076770), which book is hereby incorporated by reference in its entirety.

The TCD 100 may be configured to transmit (e.g., broadcast, multicast, transmit otherwise) through a transmitter 120B information regarding its state and expected changes in the state. The state information may include data specific to different cycles of the state machine of the TCD 100. A vehicle computer may receive the signal from the TCD 100 and determine when the light in its direction of travel will allow the vehicle to proceed. The TCD 100 may also update this information in real time, based on the passage of time and the various GRs that affect its state transitions. The TCD 100 may transmit to the traffic in its vicinity confidence information regarding the states of interest and the timing of the state changes, and may do so in real time. In “real time” means within a time period that the moving traffic can use to its advantage (e.g., to shift gears, change speed, start/stop engine, engage regenerative braking, thereby improving energy efficiency or travel time), typically within two seconds, and, even better within less than one second; in embodiments, the time period is less than 200 milliseconds. Thus, the signal from the TCD 100 may carry information regarding the current state in one or several (e.g., all) of the directions of travel through the intersection controlled by the TCD 100, and the time to the next change in the one or several directions; the vehicle computer can thus control the power train (for example, in self driving cars and cars traveling with engaged cruise control or another driver-assistance device), including braking, regenerative braking, acceleration, starting/stopping of the internal combustion engine (if present in the vehicle), selection of a gear in a multi-gear transmission or selection of a gear ratio in a continuously-variable transmission, selection of a particular electrical storage device for providing motive power or for receiving regenerated electrical power, and engagement/disengagement of a clutch. In connection with the selection of the electrical power source, an inventive vehicle may have a supercapacitor power source in addition to a more conventional electrochemical rechargeable battery (e.g., Li-Ion battery). Thus, in controlling the power train, the vehicle computer can additionally use the distance estimate(s) from the TCD or another beacon.

The communications between the TCD 100 and a remote facility/resource may be effected through the receivers 120A/transmitters 120B, through separate connections that are not shown in FIG. 1 (including dedicated landline connections, cellular connections, WiFi connections to stationary hotspots, to name a few). In embodiments, however, the communications employ intermediate connections through vehicle computers in the vehicles and/or smartphones and other mobile devices of people (pedestrians/drivers/passengers) passing in the vicinity of the TCD, such as through the intersection controlled by the TCD. The TCD may transmit packets to such devices, with instructions to send the packets to the remote facility/resource. The vehicles and/or mobile devices can then use their own connections (e.g., cellular connections to the Internet) to send the packets to the remote facility/resource; if no current connection is available, a vehicle/smartphone or other similar devices with communication/processing capabilities may store the packets and transmit them to the remote facility at a later time, when a connection becomes available. The packets may be encrypted. The TCD may break up its communications into several/many packets, so that individual packets may be sent to the vehicle computers, smartphone during a short time while the vehicle computers/smartphones are in such vicinity of the TCD that reliable communications can be maintained therebetween. The remote facility/resource can transmit its communications back to the TCD in a similar manner, for example, using the vehicles from which it received the TCD packets (because such vehicles are likely to travel in the vicinity of the TCD 100) or other vehicles. The information between the TCD and the remote facility/resource may be transmitted redundantly to assure that it is received at the destination.

The features described throughout this document and all the incorporated documents may be present individually, or in any combination or permutation, except where the presence or absence of specific features (elements/steps/limitations) is inherently required, explicitly indicated, or otherwise made clear from the description. This applies whether or not features appear related to specific embodiments; thus, features of the different described embodiments may be combined.

Although the process steps and decisions (if decision blocks are present) may be described serially in this document, certain steps and/or decisions may be performed by same and/or separate elements in conjunction or in parallel, asynchronously or synchronously, in a pipelined manner, or otherwise. There is no particular requirement that the steps and decisions be performed in the same order in which this description lists them or the Figures show them, except where a specific order is inherently required, explicitly indicated, or is otherwise made clear from the context. Furthermore, not every illustrated step and decision block may be required in every embodiment in accordance with the concepts described in this document, while some steps and decision blocks that have not been specifically illustrated may be desirable or necessary for proper operation in some embodiments in accordance with the concepts. It should be noted, however, that specific embodiments/variants/implementations/examples use the particular order(s) in which the steps and decisions (if applicable) are shown and/or described.

The instructions (machine executable code) corresponding to the method steps of the embodiments, variants, implementations, and examples disclosed in this document may be embodied directly in hardware, in software, in firmware, or in combinations thereof. A software/firmware module may be stored in volatile memory, flash memory, Read Only Memory (ROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), hard disk, a CD-ROM, a DVD-ROM, or other forms of non-transitory storage medium known in the art. Exemplary storage medium or media may be coupled to one or more processors so that the one or more processors can read information from, and write information to, the storage medium or media. In an alternative, the storage medium or media may be integral with one or more processors.

This document describes in detail the inventive apparatus, methods, and articles of manufacture for operating TCDs/beacons, vehicle computers, smart phones, and related technologies. This was done for illustration purposes and, therefore, the foregoing description is not necessarily intended to limit the spirit and scope of the invention(s) described. Neither the specific embodiments of the invention(s) as a whole, nor those of its (or their, as the case may be) features necessarily limit the general principles underlying the invention(s). The specific features described herein may be used in some embodiments, but not in others, without departure from the spirit and scope of the invention(s) as set forth herein. Various physical arrangements of components and various step sequences also fall within the intended scope of the invention(s). Many additional modifications are intended in the foregoing disclosure, and it will be appreciated by those of ordinary skill in the pertinent art that in some instances some features may be employed in the absence of use of other features. The embodiments described above are illustrative and not necessarily limiting, although they or their selected features may be limiting for some claims. The illustrative examples therefore do not necessarily define the metes and bounds of the invention(s) and the legal protection afforded the invention(s). 

I claim:
 1. A traffic control device (TCD), comprising: a processing module comprising one or more processors: storage; one or more cameras, one or more visual traffic control displays; one or more interfaces to state-affecting sensors; one or more remote interfaces configured to connect to one or more remote computer systems; and one or more buses coupling the processing module to the storage, the one or more cameras, the one or more visual traffic control displays, the one or more interfaces to the state-affecting sensors, and the one or more remote interfaces, wherein the processing module is configured to: implement a state machine to control traffic through the one or more visual traffic control displays; obtain a preliminary false green request (FGR) detection; identify one or more locations that correspond to the preliminary FGR detection; obtain through the one or more cameras one or more recordings of the one or more locations, the one or more recordings corresponding to time a green request (GR) associated with the preliminary FGR detection was generated; perform first machine-processing of GR-related data comprising the one or more recordings, to attempt to determine whether the preliminary FGR detection corresponds to a real GR; if the first machine-processing indicates that the preliminary FGR detection resulted from the real GR, clear the preliminary FGR detection; if the first machine-processing does not indicate that the preliminary FGR detection resulted from the real GR, transmit through the one or more remote interfaces to the one or more remote computer systems information regarding events that caused the preliminary FGR detection, the information comprising at least some of the GR-related data, the at least some of the GR-related data comprising the one or more recordings; and clear the preliminary FGR detection, in response to receipt by the TCD of a clear signal from the one or more remote computer systems; wherein the one or more remote computer systems are configured to: receive the information from the TCD; perform additional processing of the information to attempt to determine whether the preliminary FGR detection corresponds to the real GR or an FGR; and if the additional processing indicates the preliminary FGR detection resulted from the real GR, transmit the clear signal to the TCD to cause the TCD to clear the preliminary FGR detection.
 2. A traffic management system, comprising: the TCD of claim 1; and the one or more remote computer systems; wherein: the processing module is further configured to adjust operation of the state machine to mitigate fault associated with the FGR, in response to receipt by the TCD of an adjust signal from the one or more remote computer systems; and the one or more remote computer systems are further configured to transmit the adjust signal to the TCD to cause the TCD to adjust operation of the state machine to mitigate the fault associated with the FGR, if the additional processing indicates the preliminary FGR detection resulted from the FGR.
 3. The traffic management system of claim 2, wherein the additional processing comprises second machine-processing by the one or more remote computer systems.
 4. The traffic management system of claim 2, wherein the additional processing comprises engaging by the one or more remote computer systems one or more human resources to perform human processing.
 5. The traffic management system of claim 2, wherein the additional processing comprises engaging by the one or more remote computer systems one or more human resources to perform crowdsourced resource-processing.
 6. The traffic management system of claim 2, wherein the one or more interfaces to state-affecting sensors comprise an interface to a pedestrian pushbutton.
 7. The traffic management system of claim 6, wherein the processing module is further configured to perform the first machine-processing of the one or more recordings by searching the one or more recordings for presence of a pedestrian.
 8. The traffic management system of claim 2, wherein the one or more interfaces to state-affecting sensors comprise an interlace to a vehicle sensor.
 9. The traffic management system of claim 2, wherein the one or more interfaces to state-affecting sensors comprise an interface to an inductive loop vehicle sensor, and the processing module is further configured to perform the first machine-processing of the one or more recordings by searching the one or more recordings for presence of a vehicle.
 10. The traffic management system of claim 2, wherein the one or more remote computer systems are further configured to perform the additional processing by searching the one or more recordings for presence of a pedestrian or a vehicle.
 11. The traffic management system of claim 10, wherein the one or more recordings comprise one or more visual recordings and one or more recordings selected from the group consisting of infrared recordings and ultraviolet recordings.
 12. The traffic management system of claim 10, wherein the one or more recordings comprise one or more visual recordings and one or more recordings selected from the group consisting of lidar output recordings and radar output recordings.
 13. The traffic management system of claim 10, wherein the TCD further comprises a sound recording device, the processing module is further configured to make sound recordings corresponding to the time the GR associated with the preliminary FGR detection was generated, and the at least some of the GR-related data further comprises the sound recordings.
 14. The traffic management system of claim 2, wherein: the TCD comprises one or more radio frequency receivers and one or more radio frequency transmitters, and the processing module is further configured to connect through the one or more radio frequency receivers and the one or more radio frequency transmitters to mobile devices in a vicinity of the TCD to obtain additional recordings of the one or more locations, and the at least some of the GR-related data comprises the additional recordings.
 15. The traffic management system of claim 2, wherein: the TCD comprises one or more radio frequency receivers and one or more radio frequency transmitters, and the TCD and the one or more remote computer systems are further configured to implement the one or more remote interfaces to include means for communication between the TCD and the one or more remote computer systems via vehicles and/or mobile devices passing in a vicinity of the TCD.
 16. The traffic management system of claim 2, wherein the TCD and the one or more remote computer systems comprise means for detecting and verifying undetected true green requests.
 17. The traffic management system of claim 2, wherein the TCD comprises a radio frequency transmitter, and the TCD is further configured to implement beacon means for facilitating distance measurement between a point in a vicinity of the TCD and the TCD using transmissions of a radio frequency carrier modulated with at least three low frequencies and measurement of at least two phase differences of the at least three low frequencies at the point.
 18. An apparatus comprising: the traffic management system of claim 17; and a vehicle computer comprising a processor and a vehicle radio frequency receiver that enables the vehicle computer to receive the transmissions of the radio frequency carrier modulated with the at least three low frequencies and measure the at least two phase differences of the at least three low frequencies, the processor implementing means for measuring distance to the TCD based on the at least two phase differences.
 19. The traffic management system of claim 2, wherein: the TCD further comprises a radio frequency transmitter coupled to the processing module by the one or more buses; and the processing module is further configured to cause the TCD to transmit in real time through the radio frequency transmitter state information describing current state of the one or more visual traffic control displays and time to changes in the state of the one or more visual traffic control displays.
 20. A vehicle power train control system comprising the traffic management system of claim 19 and a vehicle computer configured to control power train functions of a vehicle, the vehicle computer comprising a processor and a vehicle radio frequency receiver that enables the vehicle computer to receive the state information and the time to changes in the state, and to vary operation of power train of the vehicle in response to changes in the state and/or the time to changes in the state. 